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Visible Machine Learning for Biomedicine
2018
Cell
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.
doi:10.1016/j.cell.2018.05.056
pmid:29906441
pmcid:PMC6483071
fatcat:47fodugzonbfze3ad5bgjx5hta