Sepsis mortality prediction with Machine Learning Tecniques.

Journal: Medicina intensiva

Published Date: Jun 13, 2024

Abstract

OBJECTIVE: To develop a sepsis death classification model based on machine learning techniques for patients admitted to the Intensive Care Unit (ICU).

Authors

Javier Carrillo Pérez-Tome

Department of Nursing: Physiotherapy and Medicine, University of Almeria, 04120 Almeria, Spain.
Tesifón Parrón-Carreño

Department of Nursing: Physiotherapy and Medicine, University of Almeria, 04120 Almeria, Spain.
Ana Belen Castaño-Fernández

Department of Applied Mathematics, University of Almería, 04120 Almeria, Spain.
Bruno José Nievas-Soriano

Department of Nursing: Physiotherapy and Medicine, University of Almeria, 04120 Almeria, Spain.
Gracia Castro-Luna

Department of Nursing: Physiotherapy and Medicine, University of Almeria, 04120 Almeria, Spain. Electronic address: graciacl@ual.es.

Keywords

Aged Cross-Sectional Studies Databases, Factual Female Hospital Mortality Humans Intensive Care Units Lactic Acid Machine Learning Male Middle Aged Sensitivity and Specificity Sepsis Spain

External Resources

View on PubMed Access via DOI PubMed (38876921)

Sepsis mortality prediction with Machine Learning Tecniques.

Abstract

Authors

Keywords

External Resources

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