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How Machine Learning Will Transform Biomedicine.
Goecks, Jeremy; Jalili, Vahid; Heiser, Laura M; Gray, Joe W.
Afiliación
  • Goecks J; Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR, USA. Electronic address: goecksj@ohsu.edu.
  • Jalili V; Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR, USA.
  • Heiser LM; Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR, USA.
  • Gray JW; Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR, USA.
Cell ; 181(1): 92-101, 2020 04 02.
Article en En | MEDLINE | ID: mdl-32243801
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.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Medicina de Precisión / Aprendizaje Automático Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Cell Año: 2020 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Medicina de Precisión / Aprendizaje Automático Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Cell Año: 2020 Tipo del documento: Article