Visible Machine Learning for Biomedicine

Cell. 2018 Jun 14;173(7):1562-1565. doi: 10.1016/j.cell.2018.05.056.


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.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Algorithms
  • Biomedical Research
  • Computational Biology / methods*
  • Machine Learning*