Leveraging machine learning for precision medicine: a predictive model for cognitive impairment in cholestasis patients
The developed LightGBM-based model effectively predicts cognitive impairment in cholestasis patients, providing actionable insights for early intervention. Integrating this tool into clinical workflows can enhance precision medicine and improve outcomes in this high-risk population.
Authors
- Xuerong Zhang (ORCID: https://orcid.org/0000-0003-1898-6771)
- Lanlan Xu (ORCID: https://orcid.org/0000-0002-8149-6065)
- Lina Zhang (ORCID: https://orcid.org/0000-0003-1783-3458)
- Fang Cheng (ORCID: https://orcid.org/0000-0003-2121-2013)
- Yongsheng He (ORCID: https://orcid.org/0000-0002-5685-7746)
- Xiaojuan Xing
Institutions
- Qingzhou City People's Hospital (CN)
Publication Details
- Journal
- BMC Gastroenterology
- Published
- 2025-03-18
- DOI
- https://doi.org/10.1186/s12876-025-03711-7
- Citations
- 2
- Primary Topic
- Pediatric Hepatobiliary Diseases and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 4.01