Accessibility settings

This paper is in the following e-collection/theme issue:

Geroinformatics and Electronic Clinical Information/Decision Making in Geriatrics (50) Clinical Information and Decision Making (2120) Machine Learning (2273) Postoperative Cognitive Dysfunction (POCD) (9) Precision Medicine (194)

Published on in Vol 9 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/78495, first published .
Integrated High-Throughput Targeted Metabolomics and Machine Learning for Early Prediction and Prevention of Postoperative Delirium in Older Adult Surgical Patients: Prospective Multicenter Cohort Study

Integrated High-Throughput Targeted Metabolomics and Machine Learning for Early Prediction and Prevention of Postoperative Delirium in Older Adult Surgical Patients: Prospective Multicenter Cohort Study

Integrated High-Throughput Targeted Metabolomics and Machine Learning for Early Prediction and Prevention of Postoperative Delirium in Older Adult Surgical Patients: Prospective Multicenter Cohort Study

Authors of this article:

Gengrui Zhong1 Author Orcid Image ;   Xiaoli Huang2 Author Orcid Image ;   Congye Li1 Author Orcid Image ;   Deqiang Wang3 Author Orcid Image ;   Dingding Huang4 Author Orcid Image ;   Menghan Sun5 Author Orcid Image ;   Quanhong Zhou1 Author Orcid Image ;   Yong Guo1 Author Orcid Image
Article Authors Cited by Tweetations Metrics

There are no citations yet available for this article according to Crossref .