Systematic review of machine learning models for personalised dosing of heparin.

Falconer, Nazanin; Abdel-Hafez, Ahmad; Scott, Ian A; Marxen, Sven; Canaris, Stephen; Barras, Michael

Falconer, Nazanin; Abdel-Hafez, Ahmad; Scott, Ian A; Marxen, Sven; Canaris, Stephen; Barras, Michael.

Afiliação

Falconer N; Department of Pharmacy, Princess Alexandra Hospital, Brisbane, Queensland, 4102, Australia.
Abdel-Hafez A; School of Pharmacy, The University of Queensland, Brisbane, Queensland, 4102, Australia.
Scott IA; Centre for Health Services Research, The University of Queensland, Level two, Building 33, Princess Alexandra Hospital, Brisbane, 4102, Australia.
Marxen S; Clinical Informatics, Princess Alexandra Hospital, Brisbane, Queensland, 4102, Australia.
Canaris S; Department of Internal Medicine and Clinical Epidemiology, Princess Alexandra Hospital, Brisbane, Queensland, Australia.
Barras M; School of Clinical Medicine, Faculty of Medicine, The University of Queensland, 4102, Australia.

Br J Clin Pharmacol ; 87(11): 4124-4139, 2021 11.

Article em En | MEDLINE | ID: mdl-33835524

Assuntos

Inteligência Artificial; Heparina; Anticoagulantes; Heparina/efeitos adversos; Humanos; Aprendizado de Máquina; Tempo de Tromboplastina Parcial

Palavras-chave

UFH; dose prediction; machine learning algorithm; predictive model; unfractionated heparin

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Heparina Tipo de estudo: Prognostic_studies / Systematic_reviews Limite: Humans Idioma: En Revista: Br J Clin Pharmacol Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Austrália

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