Study on influencing factors of age-adjusted Charlson comorbidity index in patients with Alzheimer's disease based on machine learning model
The results of this study indicate that the features screened by LASSO regression have the best predictive performance and can significantly improve the predictive ability of aCCI related comorbidities in AD patients. The column chart constructed based on this feature factor provides theoretical guidance for personalized management and precise treatment of AD patients.
Authors
- Yiming Liu (ORCID: https://orcid.org/0000-0001-7200-7197)
- Jian Ding (ORCID: https://orcid.org/0000-0002-5851-1802)
- Zheng Long (ORCID: https://orcid.org/0000-0001-6744-8078)
- Min Wang (ORCID: https://orcid.org/0000-0003-2052-199X)
Institutions
- Shandong University (CN)
- Capital Medical University (CN)
- Second Hospital of Shandong University (CN)
- Shanghai Public Health Clinical Center (CN)
- Qilu Hospital of Shandong University (CN)
Publication Details
- Journal
- Frontiers in Medicine
- Published
- 2025-01-27
- DOI
- https://doi.org/10.3389/fmed.2025.1497662
- Primary Topic
- Dementia and Cognitive Impairment Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00