Machine learning to predict adverse drug events based on electronic health records: a systematic review and meta-analysis.

Journal: The Journal of international medical research

PMID: 39668733

Abstract

OBJECTIVE: This systematic review aimed to provide a comprehensive overview of the application of machine learning (ML) in predicting multiple adverse drug events (ADEs) using electronic health record (EHR) data.

Authors

Qiaozhi Hu

Department of Pharmacy, West China Hospital, Sichuan University, Chengdu, China.
Jiafeng Li
Xiaoqi Li

West China School of Medicine, Sichuan University, Chengdu, Sichuan, China.
Dan Zou

Department of Medical Oncology, The Second Affiliated Hospital, Guizhou Medical University, Kaili, China.
Ting Xu

Bioresources Green Transformation Collaborative Innovation Center of Hubei Province, College of Life Sciences, Hubei University, Wuhan 430062, Hubei, China.
Zhiyao He

Department of Pharmacy, West China Hospital, Sichuan University, Chengdu, Sichuan, China.

Keywords

Area Under Curve Drug-Related Side Effects and Adverse Reactions Electronic Health Records Humans Machine Learning Risk Factors ROC Curve Support Vector Machine

External Resources

View on PubMed Access via DOI PubMed (39668733)

Machine learning to predict adverse drug events based on electronic health records: a systematic review and meta-analysis.

Abstract

Authors

Keywords

External Resources

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