How Machine Learning Will Transform Biomedicine

Jeremy Goecks, Vahid Jalili, Laura M. Heiser, Joe W. Gray

Research output: Contribution to journalReview articlepeer-review

206 Scopus citations


This Perspective explores the application of machine learning toward improved diagnosis and treatment. We outline a vision for how machine learning can transform three broad areas of biomedicine: clinical diagnostics, precision treatments, and health monitoring, where the goal is to maintain health through a range of diseases and the normal aging process. For each area, early instances of successful machine learning applications are discussed, as well as opportunities and challenges for machine learning. When these challenges are met, machine learning promises a future of rigorous, outcomes-based medicine with detection, diagnosis, and treatment strategies that are continuously adapted to individual and environmental differences.

Original languageEnglish (US)
Pages (from-to)92-101
Number of pages10
Issue number1
StatePublished - Apr 2 2020

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)


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