Machine learning to identify precachexia and cachexia: a multicenter, retrospective cohort study
We developed two models for identifying precachexia and cachexia, which will help clinicians detect and diagnose precachexia.
Authors
- Shiqi Lin (ORCID: https://orcid.org/0000-0001-7388-8651)
- Hailun Xie (ORCID: https://orcid.org/0009-0001-1770-5651)
- Hanping Shi (ORCID: https://orcid.org/0000-0003-4514-8693)
- Heyang Zhang (ORCID: https://orcid.org/0000-0002-6047-6874)
- Chenan Liu (ORCID: https://orcid.org/0000-0001-6089-2686)
- Tong Liu (ORCID: https://orcid.org/0000-0003-0482-0738)
- Yue Chen (ORCID: https://orcid.org/0000-0003-4424-2098)
- Xin Zheng (ORCID: https://orcid.org/0000-0003-0915-7787)
- Ziwen Wang (ORCID: https://orcid.org/0000-0001-9798-7021)
- Xiaoyue Liu (ORCID: https://orcid.org/0000-0002-1087-1235)
- Li Deng (ORCID: https://orcid.org/0000-0002-7742-0826)
- Jinyu Shi (ORCID: https://orcid.org/0000-0002-0111-2050)
Institutions
- Capital Medical University (CN)
- National Cancer Registry (IE)
- Centre for Genomic Regulation (ES)
- Beijing Shijitan Hospital (CN)
Publication Details
- Journal
- Supportive Care in Cancer
- Published
- 2024-09-03
- DOI
- https://doi.org/10.1007/s00520-024-08833-4
- Citations
- 4
- Primary Topic
- Nutrition and Health in Aging
- Type
- article
- Field-Weighted Citation Impact
- 1.31
Funders
- National Natural Science Foundation of China
- National Key Research and Development Program of China