Early prediction of in-hospital mortality utilizing multivariate predictive modelling of electronic medical records and socio-determinants of health of the first day of hospitalization

Early prediction of in-hospital mortality utilizing multivariate predictive modelling of electronic medical records and socio-determinants of health of the first day of hospitalization

Abstract Background In France an average of 4% of hospitalized patients die during their hospital stay. To aid medical decision making and the attribution of resources, within a few days of admission the identification of patients at high risk of dying in hospital is essential. Methods We used de-id...

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Bibliographic Details
Main Authors: Daniel Stoessel, Rui Fa, Svetlana Artemova, Ursula von Schenck, Hadiseh Nowparast Rostami, Pierre-Ephrem Madiot, Caroline Landelle, Fréderic Olive, Alison Foote, Alexandre Moreau-Gaudry, Jean-Luc Bosson
Format: Article
Language:English
Published: BMC 2023-11-01
Series:BMC Medical Informatics and Decision Making
Subjects:
All-cause in-hospital mortality
Data at hospital admission
Machine learning
Clinical decision making
Online Access:https://doi.org/10.1186/s12911-023-02356-4

Internet

https://doi.org/10.1186/s12911-023-02356-4

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