Automatic Cardiopulmonary Endurance Assessment: A Machine Learning Approach Based on GA-XGBOOST.

Deng, Jia; Fu, Yan; Liu, Qi; Chang, Le; Li, Haibo; Liu, Shenglin

Deng, Jia; Fu, Yan; Liu, Qi; Chang, Le; Li, Haibo; Liu, Shenglin.

Afiliação

Deng J; School of Mechanical Science & Technology, Huazhong University of Science and Technology, Wuhan 430074, China.
Fu Y; School of Mechanical Science & Technology, Huazhong University of Science and Technology, Wuhan 430074, China.
Liu Q; School of Mechanical Science & Technology, Huazhong University of Science and Technology, Wuhan 430074, China.
Chang L; York Region Secondary Virtual School, York Region, Markham, ON L3R 3Y3, Canada.
Li H; Shenzhen Rehabilitation & Aiding Devices Industry Association, Shenzhen 518000, China.
Liu S; Wuhan Union Hospital, Wuhan 430022, China.

Diagnostics (Basel) ; 12(10)2022 Oct 19.

Article em En | MEDLINE | ID: mdl-36292227

Palavras-chave

CPET; XG-BOOST; cardiopulmonary assessment

Texto completo

Adicionar na Minha BVS

Imprimir

XML

PubMed Links

Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Diagnostics (Basel) Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China País de publicação: Suíça

Texto completo

Adicionar na Minha BVS

Imprimir

XML

PubMed Links

Buscar no Google