Three Challenges for Artificial Intelligence in Medicine

Imagine yourself as a young graduate student in Stanford’s Artificial Intelligence lab, building a system to diagnose a common infectious disease. After years of sweat and toil, the day comes for the test: a head-to-head comparison with five of the top human experts in infectious disease. Over the first expert, your system squeezes a narrow victory, winning by just 4%. It beats the second, third, and fourth doctors handily. Against the fifth, it wins by an astounding 52%. Would you believe such a system exists already? Would you believe it existed in 1979? This was the MYCIN project, and in spite of the excellent research results, it never made its way into clinical practice. [1] In fact, although we’re surrounded by fantastic applications of modern AI, particularly deep learning — self-driving cars,…

Link to Full Article: Three Challenges for Artificial Intelligence in Medicine

Pin It on Pinterest

Share This