High-dimensional machine learning to predict hospital readmission among older people with chronic kidney disease: abridged secondary publication.

Zhang, Q; Leung, E; Lau, J T F; Tsoi, K K F; So, H Y; Ho, W W S; Cheung, S C Y

Zhang, Q; Leung, E; Lau, J T F; Tsoi, K K F; So, H Y; Ho, W W S; Cheung, S C Y.

Afiliação

Zhang Q; School of Data Science, City University of Hong Kong, Hong Kong SAR, China.
Leung E; The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong SAR, China.
Lau JTF; The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong SAR, China.
Tsoi KKF; The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong SAR, China.
So HY; Department of Quality and Safety, Prince of Wales Hospital, Hong Kong SAR, China.
Ho WWS; Department of Medicine and Therapeutics, Prince of Wales Hospital, Hong Kong SAR, China.
Cheung SCY; Department of Medicine, Queen Elizabeth Hospital, Hong Kong SAR, China.

Hong Kong Med J ; 29 Suppl 1(1): 24-26, 2023 02.

Article em En | MEDLINE | ID: mdl-36919215

Assuntos

Readmissão do Paciente; Insuficiência Renal Crônica; Humanos; Idoso; Medição de Risco; Fatores de Risco; Insuficiência Renal Crônica/terapia; Aprendizado de Máquina

Buscar no Google

Imprimir

XML

PubMed Links

Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Readmissão do Paciente / Insuficiência Renal Crônica Tipo de estudo: Etiology_studies / Prognostic_studies / Risk_factors_studies Limite: Aged / Humans Idioma: En Revista: Hong Kong Med J Ano de publicação: 2023 Tipo de documento: Article

Buscar no Google

Imprimir

XML

PubMed Links