A machine learning framework supporting prospective clinical decisions applied to risk prediction in oncology.

Coombs, Lorinda; Orlando, Abigail; Wang, Xiaoliang; Shaw, Pooja; Rich, Alexander S; Lakhtakia, Shreyas; Titchener, Karen; Adamson, Blythe; Miksad, Rebecca A; Mooney, Kathi

Coombs, Lorinda; Orlando, Abigail; Wang, Xiaoliang; Shaw, Pooja; Rich, Alexander S; Lakhtakia, Shreyas; Titchener, Karen; Adamson, Blythe; Miksad, Rebecca A; Mooney, Kathi.

Afiliación

Coombs L; Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, USA.
Orlando A; University of North Carolina-Chapel Hill, Lineberger Cancer Institute, Chapel Hill, NC, USA.
Wang X; Flatiron Health, Inc, New York, NY, USA.
Shaw P; Flatiron Health, Inc, New York, NY, USA.
Rich AS; Flatiron Health, Inc, New York, NY, USA.
Lakhtakia S; Flatiron Health, Inc, New York, NY, USA.
Titchener K; Flatiron Health, Inc, New York, NY, USA.
Adamson B; Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, USA.
Miksad RA; Flatiron Health, Inc, New York, NY, USA.
Mooney K; Flatiron Health, Inc, New York, NY, USA. ramiksad@flatiron.com.

NPJ Digit Med ; 5(1): 117, 2022 Aug 16.

Article en En | MEDLINE | ID: mdl-35974092

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Texto completo: 1 Base de datos: MEDLINE Tipo de estudio: Etiology_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: NPJ Digit Med Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos

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