As Deep Learning Comes For Medicine How Do We Work Around Its Brittleness?

Deep learning is revolutionizing medicine. Algorithms are increasingly doing everything from triaging medical imagery to predicting treatment outcomes. Yet as hospitals undergo the same AI revolution affecting other fields, the dangers of AI bias and errors and the life-or-death consequences of medicine lends unique risk to these experiments, suggesting caution. One of the fastest-growing uses of AI in medicine today is the analysis of medical imagery. Human analysis of imagery is slow, difficult to scale and error-prone.