Establishment of ICU Mortality Risk Prediction Models with Machine Learning Algorithm Using MIMIC-IV Database

Establishment of ICU Mortality Risk Prediction Models with Machine Learning Algorithm Using MIMIC-IV Database

Objective: The mortality rate of critically ill patients in ICUs is relatively high. In order to evaluate patients’ mortality risk, different scoring systems are used to help clinicians assess prognosis in ICUs, such as the Acute Physiology and Chronic Health Evaluation III (APACHE III) and the Logi...

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Bibliographic Details
Main Authors: Li, L. (Author), Liu, X. (Author), Ouyang, W. (Author), Pang, K. (Author), Tang, Y. (Author)
Format: Article
Language:English
Published: MDPI 2022
Subjects:
adult
APACHE
article
calibration
clinical assessment
clinical evaluation
controlled study
critically ill patient
cross validation
decision tree
diagnostic test accuracy study
female
human
intensive care
machine learning
major clinical study
male
medical information
mortality
mortality risk
organ dysfunction score
outcome assessment
postoperative death
prediction
prediction model
predictive value
prognosis
randomized controlled trial
receiver operating characteristic
risk assessment
scoring system
sensitivity and specificity
support vector machine
survival
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