A prediction model for the risk of developing mild cognitive impairment in older adults with sarcopenia: evidence from the CHARLS
This deep learning model effectively predicts MCI risk in individuals with sarcopenia, facilitating early interventions. Its accuracy aids in identifying high-risk individuals, potentially enhancing patient care.
Authors
- Rui Yin (ORCID: https://orcid.org/0000-0002-8320-1208)
- Lu You (ORCID: https://orcid.org/0000-0002-9400-2060)
- Zhenggang Wu (ORCID: https://orcid.org/0000-0003-0898-035X)
- Yan Cao (ORCID: https://orcid.org/0000-0003-4902-2297)
- Qi Chu (ORCID: https://orcid.org/0000-0003-3028-0755)
- Chenbo Ji (ORCID: https://orcid.org/0000-0002-9869-4228)
- Jinlin Tang
- Junjun Ni (ORCID: https://orcid.org/0000-0001-8486-8146)
- B. Wang (ORCID: https://orcid.org/0000-0003-4370-879X)
- Xinyue Liu (ORCID: https://orcid.org/0000-0002-2145-1674)
Institutions
- Union Hospital (HK)
- Nanjing Medical University (CN)
Publication Details
- Journal
- Aging Clinical and Experimental Research
- Published
- 2025-03-07
- DOI
- https://doi.org/10.1007/s40520-025-02980-2
- Citations
- 2
- Primary Topic
- Nutrition and Health in Aging
- Type
- article
- Field-Weighted Citation Impact
- 2.33
Funders
- National Natural Science Foundation of China
- Nanjing Medical Science and Technique Development Foundation