How artificial intelligence — AI — will change the future of health care

Ran Kornowski

Special to the USA TODAY Network

Recent advancements in Artificial Intelligence and its health care applications have created unprecedented opportunities for the medical field. However, with such tremendous potential, the technology introduces interesting questions for the future of medicine. While the debate over these key queries is already underway, it will not stop the AI revolution in health care that is already happening. We are approaching a pivotal moment in medicine as AI and machine learning come to the fore and the medical community must discuss its impact and potential ramifications.

Doctors and scientists alike are grappling with questions surrounding the costs and benefits that AI brings to health care, including those that directly impact individual patient care, as well as those that affect the industry as a whole. While in some cases AI has already been implemented and yielded positive results at both the micro and macro levels, the fear exists that computers lack the empathy and ethics, the “bedside manner” that has been the backbone of medicine for centuries. 

AI works by trying to imitate human thinking capabilities through technological means, through what is called “machine learning.” This unique field of computer science essentially trains the algorithms to rapidly process huge amounts of data efficiently so that analysis and conclusions can be drawn, sometimes even allowing for accurate predictions based on the collected and inputted data. Imagine how 10 or 15 years ago a doctor could only diagnose based on what they remembered and experienced or could research (which could take time). Now compare that to a computer with the ability to look at a series of signs and symptoms, imaging tests and lab results and compare them to infinite medical articles and multiple other patients and come back with a result nearly instantaneously. 

AI algorithms can analyze vast amounts of medical data to help identify patterns, predict outcomes and improve patient-centered diagnostic accuracy. It can help doctors tailor treatments to individual patients, based on factors like laboratory and imaging tests, genetics, lifestyle and medical history. It can automate routine tasks, freeing health care providers to focus on more complex and value-added tasks. By assisting with accurate diagnoses and personalized treatments, AI has the potential to improve patient outcomes, prevent hospitalization and reduce mortality rates.

It is not an impossibility to think that one day very soon, AI could analyze and diagnose based on medical tests and records, body imaging, pathology tests, ECG charts, genetic tests and other lab tests. In some cases, it is already being used as a tool by physicians for helping to read and interpret tests. Some say it is likely to replace doctors in that process, thus clearing more time for them, which they can reallocate to spend more time with their patients. 

During the initial months of the COVID-19 global outbreak, AI was used by larger health systems to identify outbreaks of COVID-19 waves in advance, identify patients at greater risk for deterioration, conduct informed prioritization of antiviral treatments and administration of vaccines and antibody treatments to populations at a greater risk. This is just one example of the public health impact of AI in recent years.

With great benefit though, come the risks, most widely assumed to be data privacy and security concerns, as well as how to ensure a system of standards for AI’s implementation and algorithms across the global health care field, and the need for the technology to “think” ethically, transparently, clinically relevant and remain free from bias. While at the face of things, a computer that could analyze a multitude of factors and bring back results immediately might sound great, it does come at potentially significant hazards. 

Looking forward, AI’s impact on health will depend on the quality of the derived clinical data and the commitment of the global health systems to train and implement the systems, and how the medical field works to use AI to complement its current operations. 

While the debate surrounding how AI will shape the health care industry, and how to best implement AI into the health care setting is already underway, it will not stop AI from continuing to grow, nor from the revolution it is bringing — a world where we can anticipate and potentially implement preventative measures for many patients before the outbreak of a full-blown disease or condition, a world where we can better tailor treatments to the individual, and where automating routine tasks, like writing reports, or reading tests, could free up physicians to spend more time with individual patients or see more patients during a given workday. 

Interesting times are certainly ahead of us when it comes to AI’s integration into health care. We must work collectively toward making sure that AI complements health care systems to enable them to provide more quality care while minimizing medical errors and securing the human element that is the core of good medical practice.

Prof. Ran Kornowski, MD, FACC, FESC, is the director of cardiology at Clalit Healthcare’s Rabin Medical Center, Belinson Hospital, and HaSharon Hospital in Israel. He recently chaired Israel’s first-ever conference on AI’s impact on health care.

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