Investors have honed in on artificial intelligence as the next big thing in health care, with billions flowing into AI-enabled digital health startups in recent years. But the technology has yet to transform medicine in the way many predicted, Ben and Ruth report. "Companies come in promising the world and often don't deliver," Bob Wachter, head of the department of medicine at the University of California, San Francisco, told Future Pulse. "When I look for examples of … true AI and machine learning that's really making a difference, they're pretty few and far between. Administrators say that algorithms from third-party firms often don't work seamlessly because every health system has its own tech system, so hospitals are developing their own in-house AI.

The role of artificial intelligence, or machine learning, will be pivotal as the industry wrestles with a gargantuan amount of data that could improve -- or muddle -- health and cost priorities, according to a National Academy of Medicine Special Publication on the use of AI in health care. Yet, the current explosion of investment and development is happening without an underpinning of consensus of responsible, transparent deployment, which potentially constrains its potential. The new report is designed to be a comprehensive reference for organizational leaders, health care professionals, data analysts, model developers and those who are working to integrate machine learning into health care, said Vanderbilt University Medical Center's Michael Matheny, MD, MS, MPH, Associate Professor in the Department of Biomedical Informatics, and co-editor of AI in Healthcare: The Hope, The Hype, The Promise, The Peril. It's critical for the health care community to learn from both the successes, ...

"Listen to your patient; they are telling you the diagnosis," an aphorism attributed to Dr. William Osler, the founder of modern medicine, still holds true today. The disappearance of patients' stories from electronic health records could be one reason that artificial intelligence and machine learning have so far failed to deliver their promised revolution of health care. The medical industry's fascination with artificial intelligence is understandable. Advancements in medicine have dramatically improved patient outcomes, and there is every reason to believe that machine learning, deep learning, artificial intelligence, and the like will do the same. But before we jump on the AI bandwagon, I offer this caution: consider the source of the data it is dependent on.

You could be forgiven for thinking that AI will soon replace human physicians based on headlines such as "The AI Doctor Will See You Now," "Your Future Doctor May Not Be Human," and "This AI Just Beat Human Doctors on a Clinical Exam." But experts say the reality is more of a collaboration than an ousting: Patients could soon find their lives partly in the hands of AI services working alongside human clinicians. There is no shortage of optimism about AI in the medical community. But many also caution the hype surrounding AI has yet to be realized in real clinical settings. There are also different visions for how AI services could make the biggest impact.

The health care industry is in the business of performing miracles. Whether giving sight to the blind, helping the paralyzed walk or sequencing genes to stave off disease, today's doctors and surgeons are saving and improving lives in new ways. Society is blessed to have geniuses wearing stethoscopes and lab coats. Despite immense progress, the health care industry still struggles to answer its most pressing questions. How do we help more people live longer, healthier lives?