Medical applications for Artificial Intelligence (AI) and Deep Learning (DL) have drawn a lot of attention from investors, the media, and the public at large. Whether helping us better interpret radiological images , identify potentially harmful drug interactions , discover new therapeutic targets , or simply organize medical information , AI and DL are beginning to impact real care given to real patients. Because these systems learn from examining data, rather than being programmed to follow specific logic, it is often challenging to understand why they make the decisions they make. Furthermore, recent results suggest the role of AI in medicine is transitioning to a new phase, in which AI enables us to do more than merely solve known problems in an automated way. AI is enabling us to solve “xenocomplex” problems : problems so difficult, humans have a hard time identifying a solution or even fully articulating the problem itself. To fully translate these capabilities into better o
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