Machine Learning Prediction Models for Mechanically Ventilated Patients: Analyses of the MIMIC-III Database

Background: Mechanically ventilated patients in the intensive care unit (ICU) have high mortality rates. There are multiple prediction scores, such as the Simplified Acute Physiology Score II (SAPS II), Oxford Acute Severity of Illness Score (OASIS), and Sequential Organ Failure Assessment (SOFA), w...

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Bibliographic Details
Published in:	Frontiers in medicine Vol. 8; p. 662340
Main Authors:	Zhu, Yibing, Zhang, Jin, Wang, Guowei, Yao, Renqi, Ren, Chao, Chen, Ge, Jin, Xin, Guo, Junyang, Liu, Shi, Zheng, Hua, Chen, Yan, Guo, Qianqian, Li, Lin, Du, Bin, Xi, Xiuming, Li, Wei, Huang, Huibin, Li, Yang, Yu, Qian
Format:	Journal Article
Language:	English
Published:	Lausanne Frontiers Media SA 01.07.2021 Frontiers Media S.A
Subjects:	Blood diseases Blood pressure Creatinine death Diabetes Glucose Heart failure Hemoglobin Hypertension Hypothyroidism Intensive care intensive care unit Kidney diseases Liver diseases Machine learning mechanical ventilation Medical history Medicine Metabolism Metastasis Mortality Nervous system prediction model Respiratory failure Sepsis Software Stroke Structured Query Language-SQL Ventilators Vital signs
ISSN:	2296-858X, 2296-858X
Online Access:	Get full text
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