Cohort profile for development of machine learning models to predict healthcare-related adverse events (Demeter): clinical objectives, data requirements for modelling and overview of data set for 2016–2018

PURPOSE: In-hospital health-related adverse events (HAEs) are a major concern for hospitals worldwide. In high-income countries, approximately 1 in 10 patients experience HAEs associated with their hospital stay. Estimating the risk of an HAE at the individual patient level as accurately as possible...

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Detalles Bibliográficos
Autores principales: Artemova, Svetlana, von Schenck, Ursula, Fa, Rui, Stoessel, Daniel, Nowparast Rostami, Hadiseh, Madiot, Pierre-Ephrem, Januel, Jean-Marie, Pagonis, Daniel, Landelle, Caroline, Gallouche, Meghann, Cancé, Christophe, Olive, Frederic, Moreau-Gaudry, Alexandre, Prieur, Sigurd, Bosson, Jean-Luc
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2023
Materias:
Health Informatics
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10441093/
https://www.ncbi.nlm.nih.gov/pubmed/37591641
http://dx.doi.org/10.1136/bmjopen-2022-070929

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10441093/
https://www.ncbi.nlm.nih.gov/pubmed/37591641
http://dx.doi.org/10.1136/bmjopen-2022-070929

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