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

Clinical Information and Decision Making (1407) Machine Learning (1465) Artificial Intelligence (1371)

Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/42435, first published .
Development and Assessment of Assisted Diagnosis Models Using Machine Learning for Identifying Elderly Patients With Malnutrition: Cohort Study

Development and Assessment of Assisted Diagnosis Models Using Machine Learning for Identifying Elderly Patients With Malnutrition: Cohort Study

Development and Assessment of Assisted Diagnosis Models Using Machine Learning for Identifying Elderly Patients With Malnutrition: Cohort Study

Authors of this article:

Xue Wang1 Author Orcid Image ;   Fengchun Yang2 Author Orcid Image ;   Mingwei Zhu3, 4, 5 Author Orcid Image ;   Hongyuan Cui3, 4, 5 Author Orcid Image ;   Junmin Wei3, 4, 5 Author Orcid Image ;   Jiao Li2 Author Orcid Image ;   Wei Chen1 Author Orcid Image
Article Authors Cited by (5) Tweetations (7) Metrics

Xue Wang   1 * , BM ;   Fengchun Yang   2 * , BM ;   Mingwei Zhu   3, 4, 5 , MS ;   Hongyuan Cui   3, 4, 5 , PhD ;   Junmin Wei   3, 4, 5 , MS ;   Jiao Li   2 , PhD ;   Wei Chen   1 , PhD

1 Department of Clinical Nutrition, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China

2 Institute of Medical Information, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China

3 Department of General Surgery, Beijing Hospital, National Center of Gerontology, Beijing, China

4 Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China

5 Department of Gastrointestinal Surgery, Beijing Hospital, National Center of Gerontology, Beijing, China

*these authors contributed equally

Corresponding Author:

  • Wei Chen, PhD
  • Department of Clinical Nutrition
  • Peking Union Medical College Hospital
  • Chinese Academy of Medical Sciences and Peking Union Medical College
  • No1 Shuaifuyuan Wangfujing Dongcheng District
  • Beijing, 100730
  • China
  • Phone: 86 69154095
  • Email: txchenwei@sina.com