Excellent piece from Siddhartha Mukherjee on the state of advanced computer learning in medicine.

While this piece is very long, it is well worth the read. Mukherjee takes care to highlight the promise of computer-aided diagnosis as well as the potential pitfalls.

Sebastian Thrun, formerly of Stanford’s Artificial Intelligence Lab and Google X who has worked on machine-learning for medical diagnosis, discussing the impact of artificial intelligence in medicine:

“I’m interested in magnifying human ability,” Thrun said, when I asked him about the impact of such systems on human diagnosticians…"The industrial revolution amplified the power of human muscle. When you use a phone, you amplify the power of human speech. You cannot shout from New York to California”—Thrun and I were, indeed, speaking across that distance—“and yet this rectangular device in your hand allows the human voice to be transmitted across three thousand miles. Did the phone replace the human voice? No, the phone is an augmentation device. The cognitive revolution will allow computers to amplify the capacity of the human mind in the same manner. Just as machines made human muscles a thousand times stronger, machines will make the human brain a thousand times more powerful.” Thrun insists that these deep-learning devices will not replace dermatologists and radiologists. They will augment the professionals, offering them expertise and assistance.

We need such augmentation in medicine. The current practice of medicine is incredibly labor intensive, not only from the well known burden of paperwork and administrative tasks, but also the fundamental process of diagnosis and treatment. For complex diseases, physicians must integrate a long patient history and disease course with hundreds of clinical data points. This process is cumbersome and error-prone. The complexity of modern medicine is only going to grow and with it our need for augmented medicine.