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AI and Public Health Series: How AI can advance medical knowledge and improve the patient experience

AI and Public Health Series: How AI can advance medical knowledge and improve the patient experience


One of the most important ways that artificial intelligence (AI) and machine learning (ML) systems will improve public health is by helping medical professionals better understand information about health science and patients and then using it to improve care.

It is impossible to know exactly how much medical information exists, but some attempts have been made to provide rough estimates and also to consider how the overall corpus of medical knowledge has grown over time. This is important because a higher volume of medical knowledge can help medical professionals diagnose a condition and select a management strategy faster and more accurately. But they can only do so if this constantly growing body of information can be collected, processed, and properly understood. This is where AI/ML can play a crucial role in improving health outcomes.

Machine Learning and Medical Knowledge

In 2022, I served as a member of the U.S. Chamber of Commerce’s “AI Commission on Competition, Inclusion, and Innovation,” a group formed to study AI governance. At a spring 2022 field hearing, our Commission heard remarks from Cleveland Clinic CEO and President Tom Mihaljevic, MD, and several of his colleagues. These doctors and scientists highlighted how they were already using AI/ML to improve patient care and save lives.

Mihaljevic kicked off the hearing with an eye-opening statistic. He noted that, when he started practicing medicine in the 1980s, the overall volume of medical information doubled roughly every seven years, but, according to one study’s estimates, it is now doubling every 73 days. Other metrics on the growth of medical information support this. One notable 2010 evaluation of the rapid growth of scientific medical journals found that, “[n]ew medical articles are appearing at a rate of at least one every 26 seconds, and if a physician were to read every medical journal published they would need to read 5000 articles per day.” This led the authors to wonder if the dramatic increase in medical information was “a burden or a blessing.” Medical publishing has continued to expand since then. A recent study in Science showed that in the field of medical robotics alone, the number of scientific papers has grown exponentially from less than 10 published in 1990 to more than 5,200 in 2020.

These numbers align with broader trends in scientific publications. The authors of the book The Science of Science found that “of all scientific work ever produced, half of it has been produced in the last 12 years.” And a 2023 history of scientific journals found that “[t]he number of scientific journals has exponentially grown from 10 at the end of the 17th century to 100,000 at the end of the 20th century.” The authors estimated that 3.4 million scientific articles were published in 2020 in 46,736 active, scholarly, peer-reviewed journals. A significant number of those journals involved health sciences.

No matter how it is quantified, it is clear that medical and health-related information is exploding. The only way to take full advantage of this growing body of knowledge is with the power of AI/ML, specifically with machine-reading technologies that can more quickly sift through immense datasets to find meaningful signals in the noise. As the National Cancer Institute summarized, “[W]hat scientists are most excited about is the potential for AI to go beyond what humans can currently do themselves. AI can ‘see’ things that we humans can’t, and can find complex patterns and relationships between very different kinds of data.”

How AI Facilitates Advanced Treatments and Personalized Medicine

Being able to process and better understand the growing volume of medical information has important ramifications for patient care, especially for disease diagnosis, which will be discussed in the next installment of this series. “Artificial-intelligence algorithms are processing vast troves of data in electronic medical records, searching for patterns to predict future outcomes and recommend treatments,” noted a Wall Street Journal medical reporter. “They are creating early-warning systems to help hospital staff spot subtle but serious changes in a patient’s condition that aren’t always visible or noticed in a busy unit, and predicting which patients about to be discharged from the hospital are at highest risk of being readmitted.” This is why the authors of The Age of Scientific Wellness spoke of the rise of “centaur doctors” who, “combining the best parts of human intelligence and AI assistance, will be empowered to make bold medical decisions with far fewer unintended consequences.”

AI assistants are already being used to address the significant paperwork and filing burdens doctors and nurses face, freeing up more time for patient care and research. Many medical professionals report that they are drowning in paperwork, which leaves less time to directly help patients or pursue other tasks. One notable study found that physicians spend half their in-office time doing administrative work—mostly filling out forms—instead of interacting directly with patients. Polls reveal that two-thirds of doctors and nurses report experiencing a moderate or great deal of burnout at work and cite paperwork hassles as a major contributing factor. Given these frustrations, a shocking 43 percent of doctors polled in mid-2023 said they would either not choose to become a doctor again or were unsure if they would. New algorithmic helpers could alleviate some of these burdens. Some experts note that new AI systems “will oversee some routine aspects of health care, aiming to broaden the scope of patient engagement rather than replacing interactions with clinicians.”

AI/ML systems can also facilitate the sharing of medical knowledge across more institutions and help medical professionals care for more patients as a result. At the Cleveland Clinic hearing I attended in 2022, Mihaljevic estimated that the Clinic—one of the most important medical research facilities in the nation—was only able to reach an estimated 1.5 percent of Americans using traditional means of care. Algorithmic technologies and the sophisticated data systems that power them can help expand opportunities for Americans to access the benefits of scientific knowledge and medical care from the Cleveland Clinic and America’s many other world-class medical facilities, labs, and universities. Mihaljevic noted how Cleveland Clinic doctors and researchers are now able to share information from tissue samples with much larger teams of medical experts, all of whom can—with the help of algorithmic systems—work together at a distance to better understand and use all the information at their fingertips to help patients. Robotic surgery at a distance is also becoming possible thanks to recent advances.

Mihaljevic also highlighted AI’s potential role in improving home-based medical care, which will become an essential way to help the U.S.’s rapidly aging population in the future, regardless of where they live. This is already happening thanks in part to the rise of sensors and wearable health devices that can proactively monitor health. And although wearable technologies are currently helping many people better monitor their health and fitness, they will grow far more sophisticated thanks to AI/ML. For example, new “smart bandages” can help with wound recovery or skin disorders thanks to sensors and digital connectivity. As one doctor writes in Future Care: Sensors, Artificial Intelligence, and the Reinvention of Medicine, “Digitizing ourselves will help us move from analyzing the past to predicting the future.” The combined power of these all new tools will help doctors and scientists access and better understand massive amounts of patient and health data, meaning that “the digital revolution will help to effectively address chronic diseases that have been the health care system’s Achilles’ heel.”

Conclusion: How Public Policy Affects These Outcomes

For AI to achieve its full potential and bring about the “AI revolution in medicine” that some predict, America will need to craft policy in a way that encourages innovation while addressing the many legitimate concerns about various AI capabilities.

The overall amount of innovation we can expect to flow from this space depends on whether or not America creates a sensible innovation culture for AI. Policymakers should appreciate how AI/ML technology could be derailed through burdensome new regulatory schemes rooted in fear and overbearing compliance mandates. They must keep the dynamic effects of regulation in mind when considering new or existing policies that could unnecessarily hold back promising innovations and treatments.

The next installment in this series will examine how AI is already helping with the early detection and treatment of specific ailments and diseases that cause death and significant suffering.

Coming Soon:

  • How AI Can Help Tackle Major Causes of Suffering and Death
  • How AI Can Revolutionize Drug Discovery
  • How AI Can Make Healthcare More Affordable and Accessible
  • How the FDA Is Approaching AI/ML-Enabled Medical Devices

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