Data Book examines how artificial intelligence could have helped one of the leading physician-scientists of our time.
Eric Topol, M.D., does not need to hype up his credentials for his colleagues in healthcare. That’s because almost everyone in this space understands his contributions to medicine, from genetic research and cardiology to the brave frontiers of digital health. Earlier this year, Topol published his latest book, Deep Medicine, a bastion of evidence supporting the rise of artificial intelligence (AI) in healthcare. Strikingly, in the first chapter, he told a personal story about a post-op regimen gone wrong — and how AI might have prevented his suffering.
This week on Data Book, we welcome Eric Topol to the show. We also dive further into his experience, unraveling the story thread by thread to better understand what AI can do for healthcare, not in the future but now. And, of course, in our pursuit of clarity and calculated reasoning amid the health IT noise, we explore how AI simply cannot help healthcare. That, too, comes in the form of an anecdote from Topol.
Here’s something to consider before listening to this episode: Say your health system planned to purchase an expensive but potentially valuable AI imaging system — the kind that has been proven to read scans and identify disease more quickly and accurately than most physicians. What objective would your health system aspire to achieve through implementation? Would it be time, meaning that human and machine would work together to ultimately check more scans? Or would it be higher-quality diagnoses?
If you go by Topol’s school of thought — which, in reviewing his life’s work, has been an awfully strong guide — these AI systems should accomplish an important but often-overlooked goal. AI, he says, should allow doctors more time with patients. Algorithms should provide grounds for better care, for more empathy. Simply, the machine should enable the human to focus more on humanity.
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