Machine learning classifiers do not improve prediction of hospitalization > 2 days after fast-track hip and knee arthroplasty compared with a classical statistical risk model.

Johannesdottir, Katrin B; Kehlet, Henrik; Petersen, Pelle B; Aasvang, Eske K; Sørensen, Helge B D; Jørgensen, Christoffer C

Johannesdottir, Katrin B; Kehlet, Henrik; Petersen, Pelle B; Aasvang, Eske K; Sørensen, Helge B D; Jørgensen, Christoffer C.

Afiliação

Johannesdottir KB; Biomedical Signal Processing & AI research group, Digital Health Section, DTU Health Tech, Technical University of Denmark, Lyngby. s193086@student.dtu.dk.
Kehlet H; Section of Surgical Pathophysiology 7621, Rigshospitalet, Copenhagen
Petersen PB; Section of Surgical Pathophysiology 7621, Rigshospitalet, Copenhagen
Aasvang EK; Section of Surgical Pathophysiology 7621, Rigshospitalet, Copenhagen
Sørensen HBD; Department of Anesthesiology, Center for Cancer and Organ Diseases, Copenhagen, Denmark
Jørgensen CC; Biomedical Signal Processing & AI research group, Digital Health Section, DTU Health Tech, Technical University of Denmark, Lyngby. s193086@student.dtu.dk.

Acta Orthop ; 93: 117-123, 2022 01 03.

Article em En | MEDLINE | ID: mdl-34984485

Assuntos

Artroplastia do Joelho; Artroplastia do Joelho/efeitos adversos; Teorema de Bayes; Hospitalização; Humanos; Modelos Logísticos; Aprendizado de Máquina

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Artroplastia do Joelho Tipo de estudo: Etiology_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Acta Orthop Assunto da revista: ORTOPEDIA Ano de publicação: 2022 Tipo de documento: Article

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