Bayesian networks may allow better performance and usability than logistic regression.

Wohlgemut, Jared M; Pisirir, Erhan; Stoner, Rebecca S; Kyrimi, Evangelia; Yet, Barbaros; Marsh, William; Perkins, Zane B; Tai, Nigel R M

Wohlgemut, Jared M; Pisirir, Erhan; Stoner, Rebecca S; Kyrimi, Evangelia; Yet, Barbaros; Marsh, William; Perkins, Zane B; Tai, Nigel R M.

Afiliação

Wohlgemut JM; Centre for Trauma Sciences, Blizard Institute, Queen Mary University of London, 4 Newark Street, London, E1 2AT, UK. j.m.wohlgemut@qmul.ac.uk.
Pisirir E; Machine Intelligence and Decision Support (MInDS) Research Group, School of Electronic Engineering and Computer Science, Digital Environment Research Institute, Queen Mary University of London, London, UK.
Stoner RS; Centre for Trauma Sciences, Blizard Institute, Queen Mary University of London, 4 Newark Street, London, E1 2AT, UK.
Kyrimi E; Machine Intelligence and Decision Support (MInDS) Research Group, School of Electronic Engineering and Computer Science, Digital Environment Research Institute, Queen Mary University of London, London, UK.
Yet B; Department of Cognitive Science, Graduate School of Informatics, Middle East Technical University, Ankara, Turkey.
Marsh W; Machine Intelligence and Decision Support (MInDS) Research Group, School of Electronic Engineering and Computer Science, Digital Environment Research Institute, Queen Mary University of London, London, UK.
Perkins ZB; Centre for Trauma Sciences, Blizard Institute, Queen Mary University of London, 4 Newark Street, London, E1 2AT, UK.
Tai NRM; Royal London Hospital, Barts NHS Health Trust, London, UK.

Crit Care ; 28(1): 234, 2024 Jul 11.

Article em En | MEDLINE | ID: mdl-38992714

Assuntos

Teorema de Bayes; Humanos; Modelos Logísticos

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Teorema de Bayes Limite: Humans Idioma: En Revista: Crit Care Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Reino Unido

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