Assessment of Sepsis Risk at Admission to the Emergency Department: Clinical Interpretable Prediction Model

Assessment of Sepsis Risk at Admission to the Emergency Department: Clinical Interpretable Prediction Model

This study aims to develop an interpretable prediction model based on explainable artificial intelligence to predict bacterial sepsis and discover important biomarkers. A total of 1572 adult patients, 560 of whom were sepsis positive and 1012 of whom were negative, who were admitted to the emergency...

Full description

Bibliographic Details
Main Authors: Umran Aygun, Fatma Hilal Yagin, Burak Yagin, Seyma Yasar, Cemil Colak, Ahmet Selim Ozkan, Luca Paolo Ardigò
Format: Article
Language:English
Published: MDPI AG 2024-02-01
Series:Diagnostics
Subjects:
sepsis
machine learning
explainable artificial intelligence
biomarker
Online Access:https://www.mdpi.com/2075-4418/14/5/457

Internet

https://www.mdpi.com/2075-4418/14/5/457

Similar Items