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Healthcare Industry Leverages Artificial Intelligence

With the continuous evolvement of Artificial Intelligence, the world is being benefited to the utmost level, as the applications of Artificial Intelligence is unremitting. This technology can be operated in any sector of industry, including the healthcare industry.The advancement of technology and the AI (Artificial Intelligence), as a part of modern technology have resulted in the formation of a digital macrocosm. Artificial Intelligence, to be precise, is a programming where, there is a duplication of human intelligence incorporated in the machines and it works and acts like a human.

Artificial Intelligence is transmuting the system and methods of the healthcare industries. Artificial Intelligence and healthcare, were found together over half a century. The healthcare industries use Natural Language Process to categorise certain data patterns.Natural Language Process is the process of giving a computer, the ability to understand text and spoken words just like the same way human beings can. In the healthcare sector, it gives the effect to the clinical decision support. The natural language process uses algorithms that can mimic like human responses to conversation and queries. This NLP, just like a human can take the form of simulated mediator using algorithms to connect to the health plan members.

Artificial Intelligence can be used by the clinical trials, to hasten the searches and validation of medical coding. This can help reduce the time to start, improve and accomplish clinical trainings. In simple words medical coding is transmitting medial data about a patient into alphanumeric code.

Clinical Decisions All the healthcare sectors are overwhelmed with gigantic volumes of growing responsibility and health data. Machine learning technologies as a part of Artificial Intelligence, can be applied to the electronic health records, with the help of this the clinical professionals can hunt for proper, error-free, confirmation-based statistics that has been cured by medical professionals. Further, Natural Language Process just like the chatbots, can be used for everyday conversation where it allows the users to type questions as if they are questioning a medical professional and receive fast and unfailing answers.

Health Equity Artificial Intelligence and Machine learning algorithms can be used to reduce bias in this sector by promoting diversities and transparency in data to help in the improvement of health equity.

Medication Detection Artificial Intelligence can be used by the pharma companies, to deal with drug discoveries and thus helping in reducing the time to determine and taking drugs all the way to the market. Machine Learning and Big Data as a part of Artificial Intelligence do have the great prospective to cut down the value of new medications.

Pain Management With the help of Artificial Intelligence and by creating replicated veracities the patients can be easily distracted from their existing cause of pain. Not only this, the AI can also be incorporated for the for the help of narcotic crisis.

System Networked Infirmaries Unlike now, one big hospital curing all kind of diseases can be divided into smaller pivots and spokes, where all these small and big clinics will be connected to a single digital framework. With the help of AI, it can be easy to spot patients who are at risk of deterioration.

Medical Images and Diagnosis The Artificial Intelligence alongside medical coding can go through the images and X-rays of the body to identify the system of the diseases that is to be treated. Further Artificial Intelligence technology with the help of electronic health records is used in healthcare industry that allows the cardiologists to recognize critical cases first and give diagnosis with accuracy and potentially avoiding errors.

Health Record Analysing With the advance of Artificial Intelligence, now it is easy for the patients as well as doctors to collect everyday health data. All the smart watches that help to calculate heart rates are the best example of this technology.

This is just the beginning of Artificial Intelligence in the healthcare industry. Making a start from Natural Language process, Algorithms and medical coding, imaging and diagnosis, there is a long way for the Artificial Intelligence to be capable of innumerable activities and to help medical professionals in making superior decisions. The healthcare industry is now focusing on technological innovation in serving to its patients. The Artificial Intelligence have highly transmuted the healthcare industry, thus resulting in development in patient care.

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Acceleration of Artificial Intelligence in the Healthcare Industry - Analytics Insight

Contributed Commentary by Mona G. Flores, MD

June 24, 2021 | If theres anything the global pandemic has taught healthcare providers, it is the importance of timely and accurate data analysis and being ready to act on it. Yet these same organizations must move within the bounds of patient rights regulations, both existing and emerging, making it harder to access the data needed for building relevant artificial intelligence (AI) models.

One way to get around this constraint is de-identify the data before curating it into one centralized location where it can be used for AI model training.

An alternative option would be to keep the data where it originated and learn from this data in a distributed fashion without the need for de-identification. New companies are being created to do this, such as US startup Rhino Health. It recently raised $5 million (US) to connect hospitals with large databases from diverse patient populations to train and validate AI models using Federated Learning while ensuring privacy.

Other companies are following suit. This is hardly surprising considering that the global market for big data analytics in health care was valued at $16.87 billion in 2017 and is projected to reach $67.82 billion by 2025, according to a report from Allied Market Research.

Federated Learning Entering the Mainstream

AI already has led to disruptive innovations in radiology, pathology, genomics, and other fields. To expand upon these innovations and meet the challenge of providing robust AI models while ensuring patient privacy, more healthcare organizations are turning to federated learning.

With Federated Learning, Institutions hide their data and seek the knowledge. Federated Learning brings the AI model to the local data, trains the model in a distributed fashion, and aggregates all the learnings along the way. In this way, no data is exchanged whatsoever. The only exchange occurring is model gradients.

Federated Learning comes in many flavors. In the client-server model employed by Clara FL today, the server aggregates the model gradients it receives from all of the participating local training sites (Client-sites) after each iteration of training. The aggregation methodology can vary from a simple weighted average to more complex methods chosen by the administrator of the FL training.

The end result is a more generalizable AI model trained on all the data from each one of the participating institutions while maintaining data privacy and sovereignty.

Early Federated Learning Work Shows Promise

New York-based Mount Sinai Health Systems recently used federated learning to analyze electronic health records to better predict how COVID-19 patients will progress using the AI model and data from five separate hospitals. The federated learning process allowed the model to learn from multiple sources without exposing patient data.

The Federated model outperformed local models built using data from each hospital separately and it showed better predictive capabilities.

In a larger collaboration among NVIDIA and 20 hospitals, including Mass General Brigham, National Institutes of Health in Bethesda, and others in Asia and Europe, the work focused on creating a triage model for COVID-19. The FL model predicted on initial presentation if a patient with symptoms suspicious for COVID-19 patient will end up needing supplemental oxygen within a certain time window.

Considerations and Coordination

While Federated learning addresses the issue of data privacy and data access, it is not without its challenges. Coordination between the client sites needs to happen to ensure that the data used for training is cohesive in terms of format, pre- processing steps, labels, and other factors that can affect training. Data that is not identically distributed at the various client sites can also pose problems for training, and it is an area of active research. And there is also the question of how the US Food and Drug Administration, European Union, and other regulatory bodies around the world will certify models trained using Federated Learning. Will they require some way of examining the data that went into training to be able to reproduce the results of Federated Learning, or will they certify a model based on its performance on external data sets?

In January, the U.S. Food and Drug Administration updated its action plan for AI and machine learning in software as a medical device, underscoring the importance of inclusivity across dimensions like sex, gender, age, race, and ethnicity when compiling datasets for training and testing. The European Union also includes a right to explanation from AI systems in GDPR.

It remains to be seen how they will rule on Federated Learning.

AI in the Medical Mainstream

As Federated Learning approaches enter the mainstream, hospital groups are banking on Artificial Intelligence to improve patient care, improve the patient experience, increase access to care, and lower healthcare costs. But AI needs data, and data is money. Those who own these AI models can license them around the world or can share in commercial rollouts. Healthcare organizations are sitting on a gold mine of data. Leveraging this data securely for AI applications is a golden goose, and those organizations that learn to do this will emerge the victors.

Dr. Mona Flores is NVIDIAs Global Head of Medical AI. She brings a unique perspective with hervaried experience in clinical medicine, medical applications, and business. She is a boardcertified cardiac surgeon and the previous Chief Medical Officer of a digital health company.She holds an MBA in Management Information Systems and has worked on Wall Street. Herultimate goal is the betterment of medicine through AI. She can be reached at mflores@nvidia.com.

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Data Privacy Is Key to Enabling the Medical Community to Leverage Artificial Intelligence to Its Full Potential - Bio-IT World

Tue, Jun 22, 2021

New AtlanticistbyNick Fouriezos

Related Experts: Katherine Maher,

Courtesy: Katherine Maher

When the Turkish government asked Wikipedia to take down references to reports that Turkey was supporting militants in Syria, the online encyclopedia refusedand had its reach to more than eighty million Turkish residents cut off. While that would have been a major hit for many online media platforms, Wikipedia was uniquely positioned to weather the storm, battling in court for nearly three years until Turkeys highest court ruled in January 2020 that the governments ban violated free-expression rights.

Wikipedias success was thanks to a series of intentional organizational decisions, said Katherine Maher, who stepped down in April from her post as the Wikimedia Foundations CEO and executive director and who is now a nonresident senior fellow with the Atlantic Councils newly established Democracy & Tech Initiative. At a time when major digital platforms from Facebook and Twitter to TikTok are facing censorship around the worldparticularly in countries like India, Russia, and ChinaMaher believes for-profit media companies can learn from Wikipedias example.

It is expensive, it is hard, it takes multiple years to set up. But I know that those costs are not significantly greater than what is already being expended by these companies to manage their reputations and to manage the sort of regulatory environment, Maher said.

Maher appeared Tuesday at the 360/Open Summit, hosted by the Atlantic Councils Digital Forensic Research Lab. In conversation with NBC News senior reporter Brandy Zadrozny, Maher also spoke about how Wikipedia and other platforms can fight disinformation, increase diversity, and foster trust. As Atlantic Council CEO Frederick Kempe put it when introducing the discussion, Wikipedias unique model of volunteer editors, multiple language and other affiliate communities, and nonprofit status makes the platform a microcosm of the world.

Below are some of the key takeaways from the discussion.

Tue, Jun 22, 2021

The former Wikimedia CEO joined 360/Open Summit, hosted by the Atlantic Councils Digital Forensics Research Lab. Heres a transcript of the discussion.

TranscriptbyAtlantic Council

Nick Fouriezos is an Atlanta-based writer with bylines from every US state and six continents. Follow him on Twitter @nick4iezos.

Wed, May 5, 2021

Facebooks Oversight Board ruled Wednesday that former US President Donald Trump will remain banned from the platform for encouraging the January 6 insurrection at the US Capitol. And what consequences is it likely to have on online radicalization and the use and abuse of social media around the world?

Fast ThinkingbyAtlantic Council

Mon, Feb 1, 2021

Congress will certainly take on reforming Section 230 of the Communications Decency Act, but it should not just focus on the companies and their responsibilities. Legislators should take a good, hard look in the mirror. They must provide the guidelines that are central to reducing violent extremist content online: rules on acceptable versus forbidden online speech.

New AtlanticistbyFrances Burwell

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Former Wikipedia chief on fighting censorship and potentially paying contributors to address diversity gaps - Atlantic Council

Washington, D.C. U.S. Senator Marco Rubio (R-FL) introduced legislation to halt Big Techs censorship of Americans, defend free speech on the internet, and level the playing field to remove unfair protections that shield massive Silicon Valley firms from accountability. The Disincentivizing Internet Service Censorship of Online Users and Restrictions on Speech and Expression (DISCOURSE) Act would hold Big Tech responsible for complying with pre-existing obligations per Section 230 of the Communications Decency Act (CDA) of 1996 and clarify ambiguous terms that allow Big Tech to engage in censorship.

Specifically, the DISCOURSE Act updates the statute so that when a market-dominant firm actively promotes or censors certain material or viewpoints -- including through the manipulative use of algorithms -- it no longer receives protections. The bill also limits Section 230 immunities for large corporations that fail to live up to the statutes obligations.

Big Tech has destroyed countless Americans reputations, openly interfered in our elections by banning news stories, and baselessly censored important topics like the origins of the coronavirus, Rubio said. It is absurd that these massive companies receive special protections through Federal law, even as they tear our country apart. No more free passes -- it is time to hold Big Tech accountable for their actions.

When it was first passed in 1996, Section 230 was intended to enable internet companies to host third-party content and engage in targeted moderation of the worst content without being treated as publishers, which are generally held accountable for the content that appears in its publication. But in the 25 years since the CDAs passage, internet companies have developed from tiny start-ups that needed the protections afforded by Section 230 into some of the largest corporations on Earth.

In addition to their growth, these internet companies also changed their missions. Todays tech giants use opaque algorithms and unaccountable teams of moderators to manipulate online discourse to their worldview. The result is a highly distorted public square in which Americans are censored on a daily basis.

Industry and policy experts have lauded Rubios work and the DISCOURSE Act:

"Senator Rubio deserves a lot of credit for coming up with this innovative approach to reforming Section 230. The DISCOURSE Act holds Big Tech companies accountable not only for their censorship and viewpoint discrimination, but also for their algorithmic amplification of content. This makes perfect sense. If a Big Tech company arbitrarily picks winners and losers when it comes to speech, it is itself speaking, so why should it enjoy a special immunity from civil liability for that speech? We appreciate Senator Rubio's commitment to fighting Big Tech censorship, and we hope this legislation starts an important conversation in the months ahead." - Jon Schweppe, director of policy and government affairs, American Principles Project

"We are thankful for the hard work of Senator Marco Rubio and his staff in addressing the growing concerns of NRB Members about the power of Big Tech to censor and stifle free speech. This legislation is a great first step in ensuring digital platforms are open for free speech and the gospel. We encourage the Senate to take a very serious look at this important legislation." - Troy Miller, CEO of NRB

Oracle appreciates Sen. Rubios efforts to introduce the DISCOURSE Act, which will preserve Section 230 immunities for those upstart innovators who need it but limit the protections for dominant tech platforms, who do not.

Senator Marco Rubios proposed legislation to reform Section 230 is an important step in the right direction. The Internet Accountability Project (IAP) applauds his efforts, and we hope other Republican senators will join him.

A section-by-section overview of the bill is available here, and a one-pager is here.

Key provisions of the DISCOURSE Act are also listed below.

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Rubio Introduces Sec 230 Legislation to Crack Down on Big Tech Algorithms and Protect Free Speech - Senator Marco Rubio

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House Minority Leader Rep. Kevin McCarthy, R-Calif., unveiled plans over the weekend to hold Big Tech companies accountable for what he described as "conservative censorship" and anticompetitive practices.

In a letter to fellow Republicans on Sunday, McCarthy outlined plans that would curb existing legal protections for companies like Twitter if they censor content while making it easier for state attorneys general to bring antitrust actions against tech behemoths like Google and Amazon if they break the law.

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"For the sake of preserving free speech and a free economy, its time Big Tech faces the music," McCarthy said. "House Republicans are ready to lead."

The GOP leader pointed to 2018, when conservative figures such as Rep. Devin Nunes, R-Calif., and Donald Trump Jr. were "shadow banned" on Twitter, while Google search results for "California Republicans" compared them to Nazis.

"Since then, the examples of conservative censorship and bias across internet platforms has proliferated," the letter said. "Each one of you are all too familiar with how Big Tech and its overwhelmingly liberal executives want to set the agenda and silence conservatives."

Fox News reached out to Twitter and Google for comment, but they did not immediately respond.

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McCarthys plan, which he will be introducing this week alongside Reps. Jim Jordan, R-Ohio, and Cathy Rodgers, R-Wash., includes rolling back protections under Section 230 of the Communications Decency Act, which shields online platforms from liability regarding statements made by their users. Republicans have been arguing that social media companies like Twitter and Facebook should instead be treated more like newspapers because their history of censoring posts based on their messaging is more akin to editorial decision-making than simple enforcement of site rules.

The Republican plan, referred to as the "Framework to Stop the Bias and Check Big Tech," calls for a system of transparency, which would be implemented "by mandating that any Big Tech content moderation decisions or censorship must be listed, with specificity, on a publicly available website."

The last part of the plan addresses concerns of monopolistic practices. As an example, McCarthy claimed that Amazon, Apple and Google "use their platforms to tip the scales towards higher fees and their growing product lines," and that "just about every big technology company" copies products if they are made by competitors that they cannot just acquire.

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"We will provide an expedited court process with direct appeal to the Supreme Court and empower state attorneys general to help lead the charge against the tech giants to break them up," McCarthy said. "We will also reform the administrative state and remove impediments that delay taking action on Big Tech power."

Both parties have taken steps to rein in tech giants, but McCarthy claimed that his Democratic counterparts have not sufficiently addressed the problems, and have only exacerbated the situation.

"House Democrats have advanced a plan that not only ignores addressing conservative censorship, it makes it worse," McCarthy said. "And their plan empowers a federal bureaucracy with no accountability."

Meanwhile, as leaders in Washington look to go after the tech companies, experts have warned of the unintended consequences of passing sweeping antitrust legislation.

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"Bills under review, as currently drafted, would condemn outright specified business practices and acquisitions by big digital platforms, without any inquiry into the facts on hand," former Federal Trade Commission (FTC) general counsel and Mercatus Center senior research fellow Alden Abbott said in a Thursday statement. "As such, they would outlaw and disincentivize a great deal of behavior that may benefit consumers and drive innovation."

Abbott added that the bills would "turn enforcers into regulators," which would slow innovation and spawn "economic inefficiency, to the detriment of the American economy."

Fox Business' Audrey Conklin and Megan Henney contributed to this report.

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McCarthy unveils plans to hold Big Tech accountable and 'stop the bias' - Fox Business