Clinical study applying machine learning to detect a rare disease: results and lessons learned.

Hersh, William R; Cohen, Aaron M; Nguyen, Michelle M; Bensching, Katherine L; Deloughery, Thomas G

Hersh, William R; Cohen, Aaron M; Nguyen, Michelle M; Bensching, Katherine L; Deloughery, Thomas G.

Afiliación

Hersh WR; Department of Medical Informatics & Clinical Epidemiology, School of Medicine, Oregon Health & Science University, Portland, Oregon, USA.
Cohen AM; Department of Medical Informatics & Clinical Epidemiology, School of Medicine, Oregon Health & Science University, Portland, Oregon, USA.
Nguyen MM; Department of Medical Informatics & Clinical Epidemiology, School of Medicine, Oregon Health & Science University, Portland, Oregon, USA.
Bensching KL; Department of Medicine, School of Medicine, Oregon Health & Science University, Portland, Oregon, USA.
Deloughery TG; Department of Medicine, School of Medicine, Oregon Health & Science University, Portland, Oregon, USA.

JAMIA Open ; 5(2): ooac053, 2022 Jul.

Article en En | MEDLINE | ID: mdl-35783073

Palabras clave

acute intermittent; clinical study; electronic health records; machine learning; porphyria

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: JAMIA Open Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos

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