Bitcoin reached a new high last week ahead of the first crypto-currency trading on the Nasdaq exchange, Coinbase Global Inc. After optimistic assessments by Wall Street experts, Coinbase finished its first quarter of 2021. In contrast, prominent cryptocurrencies such as Bitcoin, Ethereum, and Dogecoin experienced significant drops in the second quarter.It is typical for numerous coins to move with the same patterns in the digital currency sector. If Bitcoin (BTC), the biggest market cap cryptocurrency, rises, other digital tokens will also grow in value. If BTC declines, other participants in the space are likely to decrease simultaneously.In recent weeks, this tendency has continued, because several cryptocurrencies have decreased more in a difficult year. However, something unusual happened as a Zycrypto.com analysis indicates: Ethereum and other Altcoins have been struck harder than Bitcoin in general, but overall, there is a massive market collapse.Almost all cryptocurrencies are trading in the red and declining. While the decline in the value of these significant currencies may appear substantial, it should come as no surprise given the extreme volatility of crypto assets.The steep decline in bitcoin and other cryptocurrencies comes from a barrage of negative headlines and triggers, ranging from Tesla CEO Elon Musk to a new wave of Chinese government restrictions. They have pounded an asset class that has been defined by high volatility since its inception. According to Reuters, Bitcoin dropped to a three-and-a-half-month low in June. The main reason cited is China's ban on financial institutions offering cryptocurrency transactions.China has prohibited the provision of any services relating to cryptocurrency transactions by banking institutions and payment firms. This means that banks and online payment channels do not offer any cryptocurrency services to customers, such as registration, trading, and clearing. China imposed such a restriction in 2017. Still, the new laws have broadened the scope of the forbidden activities compared to the previous prohibition and conjecture that 'virtual currencies have no actual value.Bitcoin and Ethereum have been declining in value since Tesla CEO Elon Musk announced this week that the electric automaker would no longer accept Bitcoin as payment, reversing a previous decision.According to Avinash Shekhar, Co-CEO of ZebPay, a roughly 40% drop in the bitcoin price from its all-time high may appear dramatic. Still, it is common in many turbulent markets, including crypto, particularly following such a strong surge. The current market downturn is a turnaround from the significant increase in the second part of last year. Since September 2020, bitcoin?s price has risen by more than 200 percent, partly driven by investment bankers, banks, and other firms who appear to use cryptocurrencies. Doges, which were enhanced by Elon Musk and Mark Cuban likes, rose on Friday by more than 110% before falling the next day. Demand was so fast for the token that Robinhood trading investors disrupted the website.<h3 id="retreats-for-corporate-backing">Retreats For Corporate Backing</h3>Part of the explanation for bitcoin's decline looks at least to be a brief reversal in cryptocurrency adoption philosophy. Elon Musk revealed earlier this year that he had purchased a balance sheet worth more than $1 billion. Numerous payment companies have declared an upgrade for additional crypto activities, and big Wall Street banks are beginning their work on their customers? crypto trading teams. Mid-April Coinbase, an exchange firm for bitcoin, was announced via a direct listing.But Musk said last week, citing environmental concerns, that Tesla no longer takes bitcoin as payment. He also suggested that Tesla didn?t sell its current Bitcoin holding, using Twitter?s emoticons to indicate the firm had "diamond hands."Furthermore, according to new JPMorgan research, institutional investors appear to have shifted away from bitcoin and gold in favor of future contracts. As a value storage, Bitcoin has been called a possible substitute for conventional currency.Increasing adoption by mainstream cryptocurrencies has inspired Bitcoin's rise, and lifted other high tokens. Crypto interest rose again, as PayPal and Square businesses started permitting bitcoin transfers on their platforms, and Wall Street corporations like Morgan Stanley began giving access to coins to some of the wealthiest customers. This is despite continued worries about their volatility and use as a payment mechanism. As the base of investors expands, governments scrutinize risks more closely surrounding the industry.The central bank of Turkey prohibited the use of crypto as a payment method on April 30, stating that there is a risk of "non-recoverable" loss of the degree of anonymity behind digital tokens. In the March article, Reuters quoted an anonymous senior government source with firsthand knowledge of this proposal proposing legislation that prohibits cryptocurrencies and punishes anybody possessing or trading such assets. India will do so.Crypto companies are strengthening their position to meet the evolving legal framework and address the continuing skepticism of digital tokens. The most passionate advocates of Bitcoin regard it as a contemporary store of value and inflation, while others are afraid that a speculative bubble is developing.<h3 id="involvement-of-skepticism-in-bitcoin">Involvement of Skepticism in Bitcoin</h3>Oh, yes, plenty. It is simpler to monitor Bitcoin's movement than to find out its value, so so many organizations, professionals, and investors are skeptical about it and the crypto-currency as a whole. So far, digital currencies have not materialized, even as a replacement for paper currency.One reason for Bitcoin?s resistance against other cryptocurrencies is that space investors might regard BTC now as the most reliable digital token. Detractors might still show significant volatility levels in BTC, but are still more common than certain others. Investors who know new, lesser, cryptocurrencies may fairly be anticipated, while the bear market is operative, to shift their cash from altcoins to bitcoin.<h3 id="what%E2%80%99s-next">What?s Next?</h3>The downturn in crypto trading is not unique, which indicates that investors might be making a movement away from more speculative businesses. In recent weeks, too, technological and growth stocks, much of which exceeded the general market substantially during the coronavirus epidemic.Notwithstanding the disruption to one of the world's largest economies, the drop is called a short-term correction in the ecosystem. "Nearly 40% of its all-time high decline in bitcoin price seems extreme, but is common in many volatile markets, including crypto, particularly following such a strong surge". This is primarily due to gains from short-term traders. This reduced pricing can be called a purchasing opportunity for long-term investors, as did MicroStrategy," said Avinash Shekhar, Co-CEO of the crypto-exchange located in India, ZebPay.

REHAN HUSAIN

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Cryptocurrency

The Fall of Crypto-currency Giants

<h3 id="what-is-cross-chain-technology">What is Cross-chain Technology</h3>Blockchain and distributed ledger technologies are growing in popularity daily. Connecting these new chains is becoming more crucial as more consumers become aware of developing technology's potential. Let's go further to understand what blockchain interoperability is why it is so critical.The number of blockchain initiatives is increasing because developers are thinking outside the box to maximize the possibilities of the technology. Additionally, the rise reflects the recognition that no one technology would be able to meet all blockchain requirements simultaneously.Cross-chain technology is becoming a primary subject of debate as to the final answer for improving blockchain interoperability. In layman's words, cross-chain technology is a relatively new concept that aims to transfer value and knowledge across distinct blockchain networks.While increased use of established networks such as Ripple, Bitcoin, and Ethereum is a positive development, it has created a slew of problems, chief among them economic and technological scaling constraints. As said before, most blockchain networks function in segregated ecosystems to serve a particular set of requirements.The cross-chains function in isolation has mostly prevented individuals from reaping the full advantages of distributed ledger technology. Due to the difficulty of various blockchains interacting with one another, individuals have been unable to reap the full benefits of blockchain technology. Cross-chain technology aims to address all of these problems by providing interoperability across blockchains, allowing them to interact and exchange information more easily.A cross-chain is the capacity of two relatively independent blockchains to communicate with one another. In other words, it enables blockchains to communicate with one another due to their uniform construction. Cross-chains overcome the constraints of a single chain.Cross-chain contact may be classified as isomorphic or heterogeneous, depending on the underlying technology. For isomorphic chains, the security method, consensus process, network architecture, and logic for verifying block creation are all consistent, making interchain communication very easy.<h3 id="cross-blockchain-compatibility">Cross Blockchain Compatibility</h3>The cross-chain protocol enables the transmission of value and information across different networks. When combined with the advantages of decentralized public chains, these protocols should create the groundwork for widespread blockchain acceptance and usage.Cross-blockchain interoperability enables the exchange of data across blockchains without the need for intermediaries. This implies that blockchains with comparable networks will be able to exchange value.When used in a business ecosystem, companies will no longer be limited to dealing with customers on the company's network. Rather than that, businesses will be able to conduct transactions with customers on other suitable blockchains. The whole procedure will occur in real-time, with no downtime or costly transaction fees. As with the Internet of value, cross-blockchain interoperability will enable blockchain networks to transmit value effectively.<h3 id="who-is-leveraging-cross-chain-technology">Who is Leveraging Cross-chain Technology?</h3>Ripple is a fantastic illustration of a blockchain project that is attempting to investigate cross-chain transactions. While it is still in its infancy, Ripple is trying to enable various digital assets across multiple blockchains.Ripple has already begun assisting banks worldwide in settling cross-border payments in several currencies and cryptocurrencies. The blockchain effort, on the other hand, has an uphill battle to perfect its cross-chain technology.Businesses are using blockchain technology to develop smart contracts that do away with the need for third-party administrators and assessors. A computer program is executed on top of the blockchain to execute smart contracts, with the parties defining the rules in advance. When these conditions are satisfied, the agreement is deemed complete and is immediately enforced.The financial sector and finance functions inside companies have made the most effective use of blockchain technology. This is the area in which this technology has advanced the most. Blockchain technology is beneficial for financial operations and business due to its smart contracts, digital payments through bitcoin, increased security and non-corruptibility, and record-keeping capabilities.<h3 id="the-importance-of-interoperability-in-the-blockchain">The Importance of Interoperability in the Blockchain</h3>The success of blockchain technology will be determined by the interoperability and integration of various blockchain networks. As a result, interoperability across blockchains refers to the idea of multiple blockchains communicating with one another to facilitate information exchange.Interoperability is the capacity to see and access data across several blockchain systems. For instance, if a user sends data to another blockchain, the receiver should read, understand, and respond efficiently. However, it is not feasible due to the inability of the Bitcoin and Ethereum blockchains to exchange information.Cross Chain technology aims to address all of these issues by increasing the interoperability of blockchains. Upcoming initiatives are gradually embracing the concept as they develop platforms capable of communicating with others without using a third person.Interoperability between blockchains should go a long way toward eliminating intermediaries or third parties associated with centralized systems. The capacity of various decentralized networks to interact directly with each other should contribute significantly to the development of completely decentralized systems.<h3 id="blockchain-interoperability-projects">Blockchain Interoperability Projects</h3>Given the increasing need to improve connectivity across different blockchain networks, numerous researchers are already working to develop appropriate solutions. As developers seek to speed blockchain adoption, blockchain interoperability initiatives are increasing day by day. Blockchain Polkadot is one of the most prominent initiatives aimed towards enhancing blockchain interoperability.PolkadotPolkadot blockchain is an elevated multi-chain platform that raises the bar for blockchain interoperability. Polkadot, the brainchild of Gavid Wood, one of Ethereum's creators, aims to improve the transmission of intelligent contract data across several blockchains. It is composed of several parachains with varying properties. Its transactions may be distributed over a large region due to the network's large number of chains. This is maintained with a high degree of transaction security.Polkadot's interoperability effort guarantees a frictionless link between private chains, public networks, oracles, and permissionless interfaces. The creators of the blockchain interoperability technologies want to create an internet in which autonomous blockchain solutions may exchange data through a Polkadot relay chain.BlocknetBlocknet's developers are presently working on developing a decentralized exchange to improve exchanging interaction. Additionally, blockchain is adopting blockchain interoperability methods that can alter our current perception of blockchain.Blocknet's goal is to decentralize all four components to create the world's first decentralized exchange. Additionally, the project's supporters are improving the cross-chain platform for use as technology.AionOnline Aion Online is another high-profile Blockchain interoperability project that aims to overcome unsolved issues surrounding blockchain network stability and compatibility. The developers want to establish Aion as the de facto standard protocol for different blockchains. The ultimate goal is to facilitate the development of effective and decentralized systems.WanchainWanchain is world?s first online blockchain system capable of interoperability and secure multi-party computation. Additionally, blockchain interoperability aims to reconstruct finance by centralizing all assets on a single blockchain. They are now implementing one of the most innovative blockchain interoperability methods available.By utilizing cutting-edge cryptography research, the blockchain interoperability project guarantees cross-chain capabilities. Additionally, it uses a unique protocol to link private, public, and consortium chains. The connectivity enables the transfer of digital assets between two distinct blockchains.Blockchain CosmosCosmos blockchain is the most underappreciated interoperability effort for blockchains. The blockchain project is vying to become the center of many initiatives. The developers have now published a software development kit they claim would solve problems of scalability and interoperability in blockchain applications.The Cosmos blockchain system comprises many autonomous blockchains named Zones connected through a central blockchain dubbed the Hub. Each Zone in this instance is powered by Tendermint Core, which allows an elevated, consistent, and secure PBFT-like consensus engine. The cosmos Hub links blockchain projects through the Inter-Blockchain communication protocol to improve interoperability.<h3 id="probable-solutions-to-blockchain-interoperability-issues">Probable Solutions to Blockchain Interoperability Issues</h3>The primary impediment to blockchain interoperability is many blockchain systems that do not communicate in the same language. To begin, many sophisticated systems in use include various degrees of smart contract functionality. Additionally, the transaction method and consensus mechanisms used in these projects vary significantly, making any interconnectivity impossible.To address some of the fundamental problems impeding blockchain interoperability, a system that allows universal communication across several blockchains is required. Additionally, open protocols and Multi Chain Frameworks are being promoted as potential answers to blockchain interoperability problems.<h3 id="open-protocols-to-improve-the-interoperability-of-blockchains">Open Protocols to Improve the Interoperability of Blockchains</h3>This, we believe, is one of the better answers for interoperability concerns. Adopting open protocols should contribute significantly to establishing standardized routes for different blockchains to interact with one another. These protocols provide a common language for blockchains, which facilitates communication.The Atomic Swap is an excellent example of an Open Protocol for blockchain interoperability. Atomic Swap, which acts as a decentralized cross-chain escrow service, enables exchanging money across two distinct blockchains, such as 1BTC for 1ETH. The whole transaction occurs without the intervention of an exchange or a middleman. Inter-ledger is another cross-chain blockchain implementation that makes use of the atomic swap protocol.<h3 id="utilization-of-multiple-chain-frameworks">Utilization of Multiple-Chain Frameworks</h3>On the other hand, multi-chain frameworks serve as open environments into which blockchains can be integrated. They are more complicated than Open Protocols. They do, however, facilitate open communication and data transfer between different blockchains.Multi Chain Frameworks enable blockchains to connect and become part of a standardized ecosystem to share data. They are often referred as Internet of blockchains since they provide unique and promising possibilities for blockchain interoperability.<h3 id="conclusion">Conclusion</h3>The cross-chain developmental efforts are currently in the experimental phase, and in the future, the promotion of cross-chain platform projects will be based on a significant landing. It will rely on the use of the application, the use of the functionality and rights of certificates, instead of simply transactions like asset chains, cross-chain forecasts, asset retention, and ultimately establishing a network of transmissions to connect the digital asset islands. In the future, PPIO will use assets on other chains to pay for storage and bandwidths and create and trade data assets via cross-chain technologies.

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Blockchain

The Language of Cryptocurrency- Cross-chain Technology

Introduction to Electronic Health RecordThe digital counterpart of the patient's paper chart is commonly known as "Electronic Health Record" -EHR. EHRs are patient-centered records in real-time that provide information for authorized users immediately and securely. EHR systems are constructed to go beyond conventional clinical data gathering and provide a wider perspective for patient care. EHRs are a crucial component of IT health and can: <ul><li>Include patient history, diagnosis, medicines, treatment plans, vaccination dates, allergies, radiological imaging, laboratory findings, and test results.</li><li>Allow the proof-based methods physicians may utilize for deciding the treatment of a patient.</li><li>Provide transparent information available in a structured manner which lowers the clinical errors and administrative costs. </li></ul>An EHR is characterized by its ability to digitally generate and manage health information by authorized personnel that can be shared with other physicians across various healthcare organizations.EHR InteroperabilityThe lack of access to medical records has been recognized as a barrier to transparent and efficient treatment for patients for a long time. While systems with electronic health records (EHR) assist in resolving this problem to an extent, many of these systems are heterogeneous and exhibit minimal interoperability within platforms, and demonstrate varying success integrating into clinical workflows. Many EHR systems are thus unable to provide key advantages of digital technologies, like data sharing capabilities, streamlining user experience, and advanced analytics. The lack of interoperability with various EHR platforms is very challenging as complex patients are present with multiple healthcare facilities in different healthcare jurisdictions.The lack of interoperability causes many problems: ? Restricted exchange of data: Currently, the EHR solutions available in the market limit patient information's open flow across different platforms. For data transfer, most vendors impose interfacing costs. A lack of data sharing also encourages repetitive investigations, consuming additional healthcare resources and potentially delaying definitive care.? The lack of a unified perspective of patients: The existing solutions provided by EHR vendors are compartmentalized, which fails to capture the entire medical journey of the patient. There is no common platform or API which enables smooth communication across different proprietary and older systems.? Lack of insights: The advantages of data mining and data storage are significantly limited by the lack of full data and reluctance on the part of EHR suppliers to provide customized interfaces.Challenges in Enabling Interoperability for EHR SystemsLack of interoperability leads to massive losses, yet the number of efforts the healthcare ecosystem is making for solving the issue is far lower than expected. Much contributes to the parties' unwillingness to interoperate with EHR systems: <ul><li>Failure to share data: Data sharing between payers and suppliers has always been a problem primarily because they operate independently and do not share common data exchange standards. This divide has produced cultural inertia in interoperability adoption for these parties. Due to the present drive towards value-based care, numerous efforts are underway to integrate care and delivery, which needs a seamless exchange of information across stakeholders. </li><li>Data security and integrity: The view of a single interoperable platform, which makes possible access to all health information in one place, raises significant issues about safety and privacy. The recent Anthem violation of medical data and WannaCry ransomware is evidence that a cyber assault is threatened. When there is interoperability, the database becomes the target for cyber attackers if the whole healthcare database is housed on a single central platform. Furthermore, it is essential for accurate health data not to be manipulated by any authorities. </li><li>Misaligned incentives: The motivations of stakeholders are not aligned with the interoperability objectives.</li></ul>? Suppliers: Currently, each EHR vendor offers its own systems. When interoperability becomes a reality, consumers will no longer find their own lock-in and will be free to pick any seller. This would weaken the competitive advantage of EHR companies and cannibalize their current income sources.? Buyers: Current users of EHR systems have spent trillions of dollars to purchase and set up traditional EHR systems. The use of an interoperable platform may force them to replace their current systems, resulting in the possible loss of trillions of dollars.<ul><li>Government regulations: Forcing system interoperability is not an option with huge numbers of stakeholders in a complex information processing environment. An actual implementation would need the buy-in of all the parties involved who should be prepared to accept specific principles of governance and commercial agreements. Nevertheless, the involvement of public authorities would be essential in the timely implementation of advice and certification criteria and standards.</li></ul>Why Chose Blockchain To Enable InteroperabilityMost organizations and academics believe blockchain technology to be one of the frontiers to address the EHR interoperability issue. Blockchain is designed to address the issue of health interoperability challenge by means of distributed ledgers, and information ecosystem similar to the healthcare landscape that spreads across different nodes (payers, providers, EHR platforms, etc.). Simply said, blockchain is an encrypted or encoded ledger that is a transaction database in the form of chain blocks. Multiple users verify these blocks via consensus methods over a public or private network. The cryptographic designs built-in blockchain technology prevents data tampering and unauthorized access.Using blockchain technology to make data accessible for patients, providers, research institutes, and public entities offer several possible advantages. The use of healthcare at the patient level is a well-known trend that has led to a large number of patient data produced through mobile apps and other digital technologies. Patients can have an active and involved role in their treatment by making healthcare information more accessible. In addition, all pertinent health information would be sent to doctors at every meeting to allow effective and customized treatment plans and eliminate the chances for duplicate investigations. Enhanced access for scientists to the anonymized medical information on a scale may lead to more rigorous studies and better evidence-based decision-making. In addition, innovative efforts from developers and pharmaceutical companies could lead to lower research and development costs by making more accessible information and consent management via a patient-facing platform, thus providing patients as well as providers with more time-to-market and cheaper products and services.Despite the advantages mentioned above, many major problems need to be addressed before using them safely and effectively. Like any technology that disrupts healthcare, blockchain must be properly assessed in light of their requirements, and providers must equip themselves to make good use of the technology. While blockchain may provide a better information platform, it is simple to believe that the aforementioned advantages are not immediately achieved when implementing a blockchain system. Although a blockchain system could facilitate sharing of information between healthcare systems, patients, providers, and governmental organizations, many technological, legal, and institutional obstacles restrict its full potential in the healthcare sector.Barriers To Blockchain AdoptionThe use of blockchain as an interoperability platform will need the resolution of several issues: ? Scalability: The EHRs include the full health records for each person, and the database continues to grow with time. Traditional blockchains have limits on the maximum transaction pace because of the fundamental nature of blocks continuing to be added to a chain structure. Due to the complicated transaction logic, Blockchain transactions need sophisticated hardware. This begs the question: can blockchain be extended quickly enough to include EHR data? ? Micropayments: The healthcare industry is being inundated with related medical equipment in the near future. Micropayments have to be enabled across various IoT manufacturers to make sure these devices constantly communicate with one other and share real-time medical data. Because the conventional blockchain requires paying a fee to the miners for their computational power, it might mean paying a fee greater than the transaction value itself when processing the micropayments through blockchain. ? Power play of miners: Validation of network members known as miners is carried out in conventional blockchain. Some of the EHR prototypes based on blockchain have stimulated the participation of public health authorities as miners and offer them access to aggregate anonymized data as mining income. This provides a way to filter or postpone specific transactions for the privileged group. Interoperable Ecosystem ? An Ideal Setup The ecosystem utilizes both the forces of blockchain and the power of computation but removes the constraints of current technologies simultaneously.The ultimate platform should be a government or a public health agency distributed public leader, which allows all ecosystem members to connect and exchange data. The public ledger will be linked to every node family, including clinics, doctors, hospitals, and medical equipment; however, data on their systems will be on the private, licensed network or in the proprietary EHR. The fundamental concept of an authorized private network is identical to that of an authorized blockchain. Blockchain platforms have a balanced set of rules to enable wider usage and flexibility to meet variations in the local practice to realize their full potential. In addition, technological solutions can be emphasized, but human aspects must be taken into account. Just as Blockchain essentially opposes a siloed, decentralized approach, solutions should be decentralized as well and involve a broad range of multidisciplinary experts, including health care professionals, legal professionals, developers of technology, and patients, so that information can be exchanged optimally while safeguarding patient safety. The advantages of utilizing blockchain to make EHR more effective are undeniable. It will lead to customized and participatory therapy alongside results-based models; helps researchers develop better goods for less expense; helps to verify claim information quickly and accurately and improves settlements; reduces fraud, and helps to comply with regulations.ConclusionThe industry continues to focus on numbers ? more patients, more consultations, additional testing, more operations, and more hospitalizations. If the balance is translated into result-based charges, patient records are encouraged ? interoperability becomes a compelling offer, and blockchain is the desired answer. It is already widely agreed that changes to the business model can only solve healthcare problems. That implies that blockchain is not far away as an essential component of the medical sector.

Blockchain interoperability in healthcare industry

What is big data?Big data is a broad term that refers to a big collection of complicated data, whether unstructured or organized, that may be efficiently utilized to reveal additional insight and address business issues that were previously unsolvable using traditional analytics or software. Typically, data scientists use artificial intelligence-powered analytics to examine these massive databases constructively in order to find relationships and correlations that might give valuable business insights.Big data in healthcare sector:In healthcare, big data refers to the application of prescriptive, predictive, and descriptive analytics services to derive actionable insights from healthcare data. Three objectives underpin big data's use in healthcare:? Improve clinical results through the use of patient data.? Boost employee productivity by using operational data;? Utilize financial data from healthcare to help a practice, hospital, or healthcare institution enhance its income stream.The "Three Vs" of big data - volume, velocity, and variety - are the pillars of big data. These three characteristics or aspects define effective big data analytics in healthcare.? Volume refers to the massive quantity of data generated by healthcare organizations via their applications, portals, websites, and EHRs (electronic health records)? The term "velocity" relates to the rate at which datasets are created and processed.? Variety refers to the numerous sorts of data that we may currently produce, collect, and evaluate.Apart from these three, big data has two new Vs: veracity and value.The term "value" refers to the monetary value of the data being created, gathered, or evaluated.Finally, but certainly not least, veracity refers to the reliability, integrity, or quality of healthcare organizations? data generation, collection, and analysis.Big data is projected to enter the healthcare industry more quickly and deeply than it does other sectors such as media, financial services, and manufacturing. Which is unsurprising given that healthcare is the largest private sector employer in the United States and accounts for 20% of GDP.Indeed, it is anticipated that the worldwide healthcare big data market would expand gradually at a compound annual growth rate (CAGR) of 22.07 percent to reach around $34 billion by 2022.Another comprehensive analysis predicts that big data in healthcare will grow at an astounding 36 percent compound annual growth rate through 2025.The term "big data in healthcare" refers to the massive amounts of health data gathered from a variety of sources, including electronic health records (EHRs), medical imaging, genetic sequencing, payor records, pharmaceutical research, wearables, and medical devices. It differs from typical computerized medical and human health data used for decision-making in three ways: It is available in unprecedented volumes; data travels at a rapid rate and encompasses the vast digital universe of the health business; and, because it originates from a variety of sources, it is extremely varied in structure and character.Applications of Big dataThe major application of big data in the field of health care sector are discussed below:1. Maintaining patient health and preventing illness and disease should always be a top concern:? Consumer gadgets such as the Fitbit activity tracker and the Apple Watch monitor an individual's physical activity and can also report on particular health trends. The resultant data is already being uploaded to cloud servers, where it is being used to tell clinicians about their patients' general health and wellness.? Fitbit has already collaborated with United Healthcare, which pays its insured members with up to $1500 per year for frequent exercise. The One Drop app from Informed Data Systems for Android and Apple is causing substantial improvements in A1c levels in persons with diabetes. Meanwhile, Apple's HealthKit, CareKit, and ResearchKit applications utilize the technology built into Apple's mobile devices to assist patients in managing their diseases and to enable researchers to collect data from hundreds of millions of users globally.2. Expanding diagnostic services enables patients to receive expert treatment more easily:Apps for mobile devices, such as Aetna's Triage, advise people about their medical conditions based on aggregated data and even recommend that they seek medical treatment depending on their input.? Apple has teamed up with Stanford researchers to examine if the Apple Watch's heart sensor can be used to detect atrial fibrillation, a disease that claims roughly 130,000 lives each year in the United States. If the gadget is successful in identifying the illness, Apple can alert wearers to the need for medical treatment.? Propeller Health utilises a Bluetooth-enabled sensor that connects to inhalers and spirometers used by individuals with asthma or COPD. The business monitors ambient conditions at sensor locations and delivers information directly to patients' phones, enabling them to gain a better understanding of the reasons of their symptoms and take preventative steps. Additionally, the business sends reminders when prescriptions should be taken. Propeller says that patients are reporting 79% fewer asthma episodes and 50% more symptom-free days as a result of its 34 peer-reviewed papers.3. Cost savings: Medical data provides clinicians with more insight, which translates into improved patient care, shorter hospital stays, and fewer admissions and readmissions.? Additionally, analysis of healthcare big data helps to a better understanding of patient cohorts at highest risk for sickness, allowing for a proactive approach to prevention. In brief, study of healthcare big data enables the identification of outlier individuals who spend much more health services than the average. It can identify methods and processes that provide inferior results or are too expensive in comparison to the results.? The knowledge gained through big data analysis provides healthcare practitioners with clinical insights that would not be available otherwise. It enables them to prescribe therapies and make clinical decisions more precisely, removing much of the guesswork associated with therapy and resulting in cheaper costs and improved patient care.Importance of big data in health care sectorYes, there is growing enthusiasm for the potential of big data in healthcare, and investment in analytics is expanding. However, according to a recent Dimensional Insight research, 56% of hospitals and healthcare institutions lack adequate big data governance or a long-term analytics strategy. Here are some of the reasons why big data is critical for healthcare:<figure class="kg-card kg-image-card"><img src="file:///C:/Users/shagu/AppData/Local/Temp/msohtmlclip1/01/clip_image001.gif" class="kg-image" alt="*" loading="lazy"></figure>Inadequate data governance results in record duplication, unclaimed reimbursements, financial benchmarking issues, and other operational inefficiencies. That is something that big data can correct!<figure class="kg-card kg-image-card"><img src="file:///C:/Users/shagu/AppData/Local/Temp/msohtmlclip1/01/clip_image001.gif" class="kg-image" alt="*" loading="lazy"></figure>Patient care is also becoming more complicated, and without adequate analytics, it becomes increasingly impossible to offer high-quality, safe, and effective patient care. Numerous healthcare companies have had inconsistencies between their clinical and accounting departments as a result of data errors and incompatibilities.<figure class="kg-card kg-image-card"><img src="file:///C:/Users/shagu/AppData/Local/Temp/msohtmlclip1/01/clip_image001.gif" class="kg-image" alt="*" loading="lazy"></figure>In healthcare, big data is widely utilized to assist in identifying and managing patients who are both high-risk and expensive.<figure class="kg-card kg-image-card"><img src="file:///C:/Users/shagu/AppData/Local/Temp/msohtmlclip1/01/clip_image001.gif" class="kg-image" alt="*" loading="lazy"></figure>Indeed, 71 percent of respondents to the aforementioned research reported seeing discrepancies between data from several sources inside their company, most notably financial, clinical, and administrative information. Additionally, 51% of executives discovered discrepancies between data from several clinical departments.<figure class="kg-card kg-image-card"><img src="file:///C:/Users/shagu/AppData/Local/Temp/msohtmlclip1/01/clip_image001.gif" class="kg-image" alt="*" loading="lazy"></figure>Additionally, big data is utilized to identify high-risk regions where patients may get more efficient treatment, thus lowering costs and increasing patient satisfaction.<figure class="kg-card kg-image-card"><img src="file:///C:/Users/shagu/AppData/Local/Temp/msohtmlclip1/01/clip_image001.gif" class="kg-image" alt="*" loading="lazy"></figure>By assisting payers and healthcare providers in identifying high-risk and costly patients, big data and analytic technologies enable these people to get appropriate intervention and save money on preventative treatment well in advance.Challenges to big data:<figure class="kg-card kg-image-card"><img src="file:///C:/Users/shagu/AppData/Local/Temp/msohtmlclip1/01/clip_image001.gif" class="kg-image" alt="*" loading="lazy"></figure>The Difficulties of Data Aggregation To begin, patient and financial information is often dispersed among many payers, hospitals, administrative offices, government organizations, servers, and file cabinets. Bringing it all together and preparing for future collaboration amongst all data providers when new data is generated takes considerable preparation. Additionally, each participating business must comprehend and agree on the kinds and formats of big data to be analyzed.<figure class="kg-card kg-image-card"><img src="file:///C:/Users/shagu/AppData/Local/Temp/msohtmlclip1/01/clip_image001.gif" class="kg-image" alt="*" loading="lazy"></figure>Management Obstacles Finally, achieving the promise of big data analytics in healthcare would require companies to change their business models. Data scientists will very certainly be required, as will IT personnel with the necessary expertise to operate the analyses.<figure class="kg-card kg-image-card"><img src="file:///C:/Users/shagu/AppData/Local/Temp/msohtmlclip1/01/clip_image001.gif" class="kg-image" alt="*" loading="lazy"></figure>The scalability of data is also a problem in this sector, that needs to be taken care of.Road aheadBig data is just now starting to transform healthcare and propel the sector ahead on a number of fronts. The advances in medicine, technology, and finance that big data in healthcare offers will enable healthcare companies to enhance patient care and generate value. However, it will need stakeholders ? providers, payers, pharmaceutical manufacturers, government and politicians, as well as scientific and research communities ? to cooperate and innovate in order to reinvent their systems' design and performance. They must develop the technical infrastructure necessary to store and consolidate the enormous amount of healthcare data expected to reach 2,314 exabytes by 2020, according to industry experts. Additionally, they must invest in human capital?information technology professionals, data scientists, data architects, and big data engineers?to lead us into this new and exciting frontier of human health and well-being.Final verdictBig data has the ability to completely transform healthcare. Healthcare companies should make significant investments in big data in order to improve patient outcomes, reduce costs, and increase efficiency across all departments. More importantly, big data will enable doctors and hospitals to provide more focused treatment with improved outcomes. For pharmaceutical firms, big data is a catalyst that will aid in the creation and development of more creative medicines and products.On a broad level, healthcare stakeholders may depend on big data and predictive analytics to address critical problems like as readmission rates, high-risk patient care, staffing difficulties, and medication mistakes.

The Role of Big-Data in Healthcare sector

IntroductionNatural language processing (NLP) refers to a computer's capacity to comprehend current human speech and writing. It is utilised in modern technology to facilitate the privacy of spam email, personal voice assistants, and language translation apps.Natural language processing is gaining traction in healthcare due to its demonstrated ability to search, analyse, and understand massive quantities of medical data. By utilising modern medical algorithms, machine learning in healthcare, and natural language processing (NLP) technology services, it is possible to extract meaningful insights and concepts from data that was previously believed to be buried in text. NLP in healthcare media can properly speak the unstructured data of the healthcare universe, providing tremendous insight into quality, technique improvement, and improved patient outcomes.Physicians spend considerable effort documenting the how and why of their patients' care in chart notes. These notes are not easily extractable in ways that allow for computer analysis of the data. When a physician consults with you and notes your visit in a case note, such narratives are entered into electronic health record systems (EHRs) and kept as free text.Analytics are already assisting providers in navigating this shift, particularly when it comes to the income and usage problems associated with transitioning away from a fee-for-service payment model.However, clinical analytics and healthcare systems have proven to be more difficult to scale. Dissatisfaction with electronic health records remains high, and is unlikely to subside as developers and regulators attempt to cram an increasing number of patient safety features, quality metrics, and reporting obligations into the same old software.Providers frequently lack access to socioeconomic, behavioural, and environmental data necessary to create truly actionable analytics at the point of care, and consumer enthusiasm for Internet of Things devices and patient-generated health data complicates the issue of delivering meaningful results to end users without hopelessly clogging the computer screen. While it may be tempting to switch off the laptop and quiet the smartphone in favour of a simpler period when the consult room comprised simply the patient, the physician, and a pad of paper, healthcare will not solve its insight issues by restricting the amount of data available to users.What is NATURAL LANGUAGE PROCESSING?Natural language processing is an umbrella phrase that refers to the practise of identifying important features in daily language and extracting meaning from unstructured spoken or written input using computer algorithms. NLP is a computer science subject that involves expertise in artificial intelligence, computational linguistics, and other areas of machine learning.Certain NLP initiatives are aimed at defeating the Turing test by developing algorithmically-based entities capable of emulating human-like replies to inquiries or dialogues. Others utilise voice recognition technology to attempt to comprehend human speech, such as the automated customer support systems used by many big corporations.Yet others are devoted to giving data to consumers by detecting and extracting critical facts from massive amounts of data, such as superhuman speed readers with near-limitless memory capacity.NLP systems may be assigned specific duties such as the following:? Summarizing extensive passages of narrative text, such as a clinical note or academic journal article, by highlighting significant themes or words found in the source material? Mapping unstructured text data components to structured fields in an electronic health record in order to improve the integrity of clinical data? Converting data from machine-readable formats to plain language for reporting and instructional purposes in the other way? Responding to unique free-text questions that necessitate the synthesis of data from different sources? Using optical character recognition to convert pictures like as PDF documents or scans of care summaries and imaging reports to text files that can be processed and analysed? Conducting voice recognition to enable users to dictate clinical notes or other data that can be converted to text? Numerous natural language processing systems "learn" over time, reabsorbing the outcomes of earlier encounters to determine which outcomes were correct and which did not match expectations.These machine learning systems can work on the basis of statistical probabilities, which weigh the probability that a particular piece of data is indeed what the user requested. Depending on whether or not the response is approved, the probability can be changed in the future to reflect the end-growing user's demands.NLP in HealthcareNatural language processing was largely an academic subject until it gained traction in the commercial sector as a result of a massive increase in computing power, the adoption of cloud computing, and significant investment by technology companies in developing algorithms that can derive meaning from human speech, according to Mahi Rayasam, a partner in McKinsey's Detroit office and co-leader of Healthcare Analytics by. ?Ten years ago, if I had spoken to the forerunner to Siri with my non-American accent, it would not have understood me. However, it now comprehends more,? he explains.On the other hand, we know that clinical data is quite complicated. Consumer data is very simple to grasp from a semantic process viewpoint, such as when you ask Siri about the local weather or tell Alexa to purchase more detergent online. However, clinical data ? such as physician notes regarding a visit, emails, and specialised pictures ? can contain essential information whose meaning is more difficult to collect via an automated approach.Interest in natural language processing applications in healthcare has increased as a result of the adoption of EHRs and the improvement in accuracy levels for improved entity extraction and document specification. While clinical NLP is shown potential in the business, it will be years before EHRs are widely used to alleviate physician fatigue.Future of NLPWhile natural language processing is not quite there yet, the healthcare sector is prepared to put in the effort necessary to get there. Cognitive computing and semantic big data analytics initiatives, both of which rely heavily on natural language processing, are getting significant investment from some well-known names.Financial analysts are positive on the prospects for natural language processing and allied technologies in the next years. According to Allied Industry Research, the cognitive computing market will reach $13.7 billion by 2020, growing at a 33.1 percent compound annual growth rate (CAGR) over current levels.Natural language processing accounted for 40% of total market revenue in 2014 and will continue to be a significant potential for the industry. Healthcare is already the most prolific consumer of these technologies and will continue to do so for the remainder of the decade.Additionally, the same organisation anticipates spending $6.5 billion on text analytics by 2020. Predictive analytics powered by unstructured data will experience considerable growth. Consumer behaviour modelling, illness tracking, and financial forecasting are all possible uses.Natural language processing techniques may eventually be able to close the gap between the unfathomable quantity of data created on a daily basis and the human mind's limited cognitive capability. From cutting-edge precision medicine applications to the routine chore of coding a claim for billing and payment, natural language processing has virtually infinite promise for transforming electronic health records from burden to boon. The industry is monitoring the growing usage of NLP applications in healthcare. According to a recent online poll conducted by John Snow Labs, 36% of respondents who work in healthcare or life sciences want to implement NLP technology by the end of 2021.Combining NLP with computer vision, for example, would enable multimodal learning approaches, which combine what a computer can see, read, and hear, Talk. The future use cases may involve "incorporating more intelligence into the search" process inside a single patient's EHR, therefore facilitating more accurate care recommendations. Additionally, natural language processing systems might be utilised to streamline administrative processes such as prior authorisation.Due to the vast volumes of data stored in healthcare systems, the integration of NLP and other AI capabilities can open up a world of possibilities for improving clinical decision-making and allowing clinicians to focus on their patients rather than their gadget displays.ConclusionThe development of improved natural language processing for healthcare data has proven difficult in 2018 and 2019. If the NLP output contains an excessive number of recommended conclusions or erroneous artificial conclusions, users will learn to disregard the intelligence, resulting in a system that can impair overall business productivity. NLP software for healthcare should prioritise data findings that include the least noise and the most information about what healthcare practitioners should do.Healthcare natural language processing enables computers to perform the tasks that computers are designed to perform. To do analytics, HCC risk adjustment coding, back-office tasks, and patient set analysis while maintaining open contact with physicians.In healthcare, natural language processing is enabling new and exciting possibilities for healthcare delivery and patient experience. It will only be a matter of time before sophisticated natural language processing code recognition enables physicians to spend more time with patients while also assisting them in making insightful decisions based on accurate facts. In the years ahead, we'll hear about and see the potential of this technology as it enables clinicians to have a beneficial impact on health outcomes.

NLP and Patient records

Coming from a synthesis of cognitive science and based on the fundamental premise of simulating the human thought process, cognitive computing as a concept and its applications are sure to have far-reaching implications for our personal lives and industries such as healthcare, insurance, and more. The advantages of cognitive technology much outweigh those of conventional artificial intelligence systems.

The Changing Scenarios of Digital Enterprises in 21st Century World

<div>Introduction In today's tech-savvy generation of modern computing inception, AI has been a far-fetched objective, yet each day appears to bring us closer to that goal with new cognitive computing models.<o:p></o:p> Coming from a synthesis of cognitive science and based on the fundamental premise of simulating the human thought process, cognitive computing as a concept and its applications are sure to have far-reaching implications for our personal lives and industries such as healthcare, insurance, and more. The advantages of cognitive technology much outweigh those of conventional artificial intelligence systems.<o:p></o:p> According to David Kenny, General Manager, IBM Watson – the world's most powerful cognitive computing framework — "AI is only as intelligent as the people who educate it." The same cannot be said of the most recent cognitive revolution.<o:p></o:p> Cognitive computing processes employ a combination of artificial intelligence, neural networks, machine learning, natural language processing, sentiment analysis, and contextual awareness to solve problems in the same way as people do. IBM defined&nbsp;cognitive computing&nbsp;as an advanced system that learned rapidly, reasoned purposefully, and interacted naturally with humans. <h4 style="margin: 0cm 0cm 8pt; line-height: 22px;">Artificial Intelligence vs. Cognitive Computing</h4>While the fundamental purpose of artificial intelligence is to find the optimal algorithm to solve a problem, cognitive computing takes a step further by attempting to replicate human intellect and wisdom via the analysis of a variety of elements. Cognitive computing is an entirely distinct notion from Artificial Intelligence.<o:p></o:p><h4 style="margin: 0cm 0cm 8pt; line-height: 22px;">Cognitive computing emulates and learns from human cognitive processes.</h4>Unlike artificial intelligence systems that solve a specific problem, cognitive computing learns through pattern analysis and offers appropriate actions to humans based on their knowledge. In the case of artificial intelligence, the system takes absolute control of a process and uses a pre-defined algorithm to finish a job or avoid a situation.<o:p></o:p>In comparison, cognitive computing is a distinct discipline in which the computer acts as assistance rather than the performer of the work. Thus, cognitive computing enables people to do faster and more accurate data analysis without worrying about the machine learning system making incorrect conclusions.<o:p></o:p><h4 style="margin: 0cm 0cm 8pt; line-height: 22px;">Cognitive computing does not obliterate people.</h4>As said previously, cognitive computing's primary goal is to aid people in decision-making. This endows humans with exceptional analytical precision while also assuring that everything remains under their control. As an illustration, consider artificial intelligence in the healthcare system. A system powered by AI would make all treatment decisions without consulting a human doctor. However, cognitive computing would enhance human diagnosis with its own set of facts and analysis, improving decision quality and adding a human touch to essential operations.<h4 style="margin: 0cm 0cm 8pt; line-height: 22px;">Going Cognitive: Cognitive Computing's Benefits</h4>Modern computer technologies are poised to transform current and historical process automation systems. According to Gartner, cognitive computing will reshape the digital world in ways that no other technology has in the past two decades. By enabling the analysis and processing of massive volumes of volumetric data, cognitive computing enables the use of a computing system for meaningful real-world applications. Cognitive computing provides a slew of advantages, among which are the following:<o:p></o:p><h4 style="margin: 0cm 0cm 8pt; line-height: 22px;">Analyze Data with Precision</h4>Cognitive systems are incredibly efficient in collecting, juxtaposing, and cross-referencing data to understand a scenario efficiently. In the healthcare industry, cognitive systems such as IBM Watson assist physicians in collecting and analyzing data from a variety of sources, including previous medical reports, medical journals, diagnostic tools, and historical data from the medical community, thereby assisting physicians in providing a data-backed treatment recommendation that benefits both the patient and the physician. Rather than replacing physicians, cognitive computing accelerates data analysis through robotic process automation.<o:p></o:p><h4 style="margin: 0cm 0cm 8pt; line-height: 22px;">Streamlined &amp; Expanded Business Processes That Are Efficient</h4>Cognitive computing enables real-time analysis of developing trends, identifying business possibilities, and resolving crucial process-centric concerns. A cognitive computing system like Watson can streamline operations, mitigate risk, and adapt to changing situations by analyzing massive amounts of data. While this equips firms to respond appropriately to uncontrolled variables, it also aids in the development of lean business processes.<o:p></o:p><h4 style="margin: 0cm 0cm 8pt; line-height: 22px;">Enhancement of Customer Interaction</h4>By incorporating robotic process automation, the technology may be leveraged to improve client relations. Customers can obtain contextual information from robots without interacting with other staff members. Because cognitive computing enables businesses to present consumers with only relevant, contextual, and meaningful information, it enhances the customer experience, increasing customer satisfaction, and engagement.<h4 style="margin: 0cm 0cm 8pt; line-height: 22px;">Cognitive Computing Issues: Obstacles to a Better Future</h4>Each new technology has challenges during its existence. Even though cognitive computing can transform lives, humans oppose innovation because of fear of change. Numerous cognitive computing drawbacks have been identified, posing substantial obstacles to broader implementation, including the following:Security When digital devices manage sensitive data, the issue of security inevitably arises. With the ability to process and analyze enormous amounts of data, cognitive computing faces substantial data security and encryption challenges.With the proliferation of connected devices, cognitive computing will need to consider the implications of a security breach by building a foolproof security strategy that includes a system for identifying suspicious behavior to maintain data integrity.Adoption The primary impediment to every new technology's success is voluntary adoption. To ensure the success of cognitive computing, it is critical to building a long-term vision for how the new technology will improve procedures and enterprises.The adoption process may be simplified by collaboration amongst many parties, including technology developers, corporations, governments, and individuals. Simultaneously, it is critical to have a data privacy policy that will further accelerate the adoption of cognitive computing.Management of Change Change management is another critical issue that cognitive computing must address. People are reluctant to change due to their inherent human nature, and because cognitive computing can learn in the same way that humans do, people are concerned that robots will eventually replace humans. This has had a significant influence on growth prospects.Cognitive technology, on the other hand, is designed to function in concert with people. By injecting information into the networks, humans will foster technology. This makes it an excellent illustration of a human-machine relationship that people must accept.Protracted Development Cycles One of the most significant obstacles is the time required to construct scenario-based applications using cognitive computing. Cognitive computing is presently being developed as a generic solution — which implies that it cannot be applied across numerous industrial segments without the support of large development teams and a significant amount of time.Protracted development cycles make it more difficult for smaller businesses to build cognitive capacities independently. With time, as development lifecycles decrease, cognitive computing will undoubtedly take on a more significant role in the future.<h4 style="margin: 0cm 0cm 8pt; line-height: 22px;">Conclusion</h4>Adoption of cognitive technology begins with the discovery of manual tasks that can be automated utilizing the technology as part of the digital evolutionary cycle. Numerous businesses, such as IBM, have previously pioneered the cognitive technology space, which is now powering a slew of genuinely digital corporations worldwide.<o:p></o:p>Each minute, additional data is evaluated to acquire insight into past occurrences and to optimize present and future activities. Not only can cognitive technology aid in prior analysis, but it also aids in far more accurate prediction of future occurrences via predictive analysis. Due to the strong and adaptable nature of the technology, the future opportunities and pathways in both the B2B and B2C segments are enormous. IBM Watson is already leveraging the power and benefits of cognitive computing in the finance and healthcare industries. It is thought that in the future, such technology would assist humans in becoming more efficient, delegating routine analysis and focusing on creative tasks.<o:p></o:p>To maximize the benefits of cognitive computing, firms must do a thorough study of their processes, data, talent model, and the market in which they operate. Beyond cost reduction, we believe that one of the greatest potentials for cognitive technology is the capacity to create value, as well as the ability to restructure work and boost efficiency by streamlining a variety of procedures.<o:p></o:p>Regardless of the difficulties and obstacles, the benefits of cognitive technology cannot be underestimated. All enterprises and humankind as a whole will benefit from initiating the transition process and adopting innovative technologies to ensure a bright and much more efficient future.<o:p></o:p></div>

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