AI and the Future of Surgery



Artificial intelligence in medicine is here. But it’s still in its infancy.

The FDA has approved about three dozen AI algorithms in medicine over the past few years, many of which aim to help physicians diagnose disease: diabetic retinopathy from retinal images, cancerous liver and lung lesions from CT and MRI scans, and breast cancer from mammograms.
Entrepreneurs and health care leaders also have jumped on board. Last year, health AI startups brought in $4 billion in funding, and a recent survey found that about half of hospital executives intend to invest in AI over the next year or two.
Although some experts predict that AI will transform medicine, others worry the buzz may be overblown. A recent headline in  The Los Angeles Times  asked, “Can AI live up to the hype?” and an article from  The Hill  explored the “Dangers of Artificial Intelligence in Medicine.”
“At the moment, the term AI is very hyped, but a lot of it is real and already translating into something tangible,” said Sandip Panesar, MD, a postdoctoral research fellow in neurosurgery at Stanford University, in California. But, he cautioned, “robots and devices that can take over human dexterity: That’s in the future. Humans will have to hold AI’s hand for a long time.”

But will AI someday replace physicians? Judith Pins, RN, MBA, the president of the health care education company Pfiedler Education, a subsidiary of the Association of periOperative Registered Nurses, does not think so. Ms. Pins, who recently spoke at a Nurse Executive Leadership Seminar on the OR of the future, sees AI as a tool that can assist providers.
“AI won’t replace doctors and nurses, but it can help make good providers great ones in terms of validating diagnoses and patient care,” she said.
Dan Hashimoto, MD, MS, a general surgery resident at Massachusetts General Hospital, in Boston, has some concerns about the hype surrounding AI in medicine. Dr. Hashimoto believes that unrealistic expectations about AI can “lead to significant disappointment and disillusionment” ( Ann Surg  2018;268[1]:70-76).
Artificial intelligence experts have seen it happen before. In the early 1990s, when advances in expert systems—AI software that can mimic the decision-making ability of a human—did not live up to the media hype, the research fizzled.
“Problems arose because we did not have enough computational power several decades ago to develop robust algorithms that could deal with large image data sets,” said Sharmila Majumdar, PhD, a professor and the vice chair of research in the Department of Radiology at the University of California, San Francisco, who launched the Artificial Intelligence Center to Advance Medical Imaging last year.
But Dr. Hashimoto—who co-directs the Surgical Artificial Intelligence and Innovation Laboratory at MGH with Ozanan Meireles, MD, an assistant professor of surgery at Harvard Medical...

Top