Machine Learning-Based Prediction Models for Delirium: A Systematic Review and Meta-Analysis.

Journal: Journal of the American Medical Directors Association

Published Date: Jul 31, 2022

OBJECTIVE: To critically appraise and quantify the performance studies by employing machine learning (ML) to predict delirium.

Qi Xie

Department of Academic Management, China Academy of Chinese Medical Sciences, Beijing, 100700, China. xieqixieqi@139.com.
Xinglei Wang

Department of Liver Diseases Branch, Lanzhou University Second Hospital, Lanzhou, Gansu, China.
Juhong Pei

The First Clinical Medical College, Lanzhou University, Lanzhou, Gansu, China.
Yinping Wu

The Medical Department of Neurology, Lanzhou University Second Hospital, Lanzhou, Gansu, China.
Qiang Guo
Yujie Su

School of Nursing, Lanzhou University, Lanzhou, Gansu, China.
Hui Yan

School of Computer Science and Engineering, Nanjing University of Science and Technology, 210094, China. Electronic address: yanhui@mail.njust.edu.cn.
Ruiling Nan

Department of EICU, Lanzhou University Second Hospital, Lanzhou, Gansu, China.
Haixia Chen

Department of Oncology Surgery, Lanzhou University Second Hospital, Lanzhou, Gansu, China.
Xinman Dou

School of Nursing, Lanzhou University, Lanzhou, Gansu, China; Department of Nursing, Lanzhou University Second Hospital, Lanzhou, Gansu, China. Electronic address: douxm@lzu.edu.cn.

Adult Delirium Humans Machine Learning Prospective Studies Reproducibility of Results ROC Curve

View on PubMed Access via DOI PubMed (35922015)