An artificial intelligence malnutrition screening tool based on electronic medical records
Inpatients' EHR data could be integrated by AI to detect the risk of malnutrition. This AI-enabled tool may hold promise for timely and efficient nutrition screening in newly admitted inpatients.
Authors
- Fang An (ORCID: https://orcid.org/0000-0003-0950-8137)
- Wanqing Zhao (ORCID: https://orcid.org/0000-0003-3705-5737)
- Wei Chen (ORCID: https://orcid.org/0000-0001-6886-9923)
- Pei Lou (ORCID: https://orcid.org/0000-0003-1426-670X)
- Kuanda Yao (ORCID: https://orcid.org/0009-0001-5737-3313)
- Yansheng Li (ORCID: https://orcid.org/0000-0001-8985-3541)
- Xue Wang (ORCID: https://orcid.org/0009-0003-5224-906X)
- Jiahui Hu (ORCID: https://orcid.org/0000-0003-4352-3250)
- Yan Liu (ORCID: https://orcid.org/0000-0002-6682-6855)
- Jin Fu
- Zhicheng Huang
Institutions
- Chinese Academy of Medical Sciences & Peking Union Medical College (CN)
- Peking Union Medical College Hospital (CN)
- Zhong Ke San Huan (China) (CN)
Publication Details
- Journal
- Clinical Nutrition ESPEN
- Published
- 2025-04-29
- DOI
- https://doi.org/10.1016/j.clnesp.2025.03.178
- Citations
- 2
- Primary Topic
- Nutrition and Health in Aging
- Type
- article
- Field-Weighted Citation Impact
- 2.33