Visible Machine Learning for Biomedicine

A major ambition of artificial intelligence lies in translating patient data to successful therapies.
Machine learning models face particular challenges in biomedicine, however, including handling
of extreme data heterogeneity and lack of mechanistic insight into predictions. Here, we argue
for ‘‘visible’’ approaches that guide model structure with experimental biology.