Predicting acute and long-term mortality in a cohort of pulmonary embolism patients using machine learning.

El-Bouri, Wahbi K; Sanders, Alexander; Lip, Gregory Y H

El-Bouri, Wahbi K; Sanders, Alexander; Lip, Gregory Y H.

Afiliação

El-Bouri WK; Liverpool Centre for Cardiovascular Science, University of Liverpool and Liverpool Heart & Chest Hospital, Liverpool, UK; Department of Cardiovascular and Metabolic Medicine, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, UK. Electronic address: w.el-bouri@liverpool.ac.uk.
Sanders A; Liverpool Centre for Cardiovascular Science, University of Liverpool and Liverpool Heart & Chest Hospital, Liverpool, UK.
Lip GYH; Liverpool Centre for Cardiovascular Science, University of Liverpool and Liverpool Heart & Chest Hospital, Liverpool, UK; Department of Cardiovascular and Metabolic Medicine, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, UK.

Eur J Intern Med ; 118: 42-48, 2023 12.

Article em En | MEDLINE | ID: mdl-37487827

Assuntos

Embolia Pulmonar; Tromboembolia Venosa; Humanos; Medição de Risco; Prognóstico; Tromboembolia Venosa/tratamento farmacológico; Índice de Gravidade de Doença

Palavras-chave

Deep vein thrombosis; Random forests; Risk stratification; Simplified pulmonary embolism severity index; Venous thromboembolism

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Embolia Pulmonar / Tromboembolia Venosa Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Eur J Intern Med Assunto da revista: MEDICINA INTERNA Ano de publicação: 2023 Tipo de documento: Article

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