Mapping the landscape of machine learning in chronic disease management: A comprehensive bibliometric study
ML is rapidly integrating into personalized medicine, real-time monitoring, and multimodal data fusion. However, challenges such as limited collaboration, weak model generalization, and data privacy persist. Future efforts should prioritize algorithm optimization and multisource data integration to advance clinical applications.
Authors
- Xiaohong Zhu (ORCID: https://orcid.org/0009-0009-6060-8134)
- Shihua Cao (ORCID: https://orcid.org/0000-0002-9391-2345)
- Sixie Li
- Bin Wang (ORCID: https://orcid.org/0009-0006-3441-9709)
- Chaoqun Dong (ORCID: https://orcid.org/0009-0002-2615-0931)
- Xin Liu (ORCID: https://orcid.org/0009-0002-2738-7674)
- Jianwen Zeng
- Qian Xu
- Shuying Shen (ORCID: https://orcid.org/0009-0006-0817-0719)
- Wenhao Qi (ORCID: https://orcid.org/0009-0001-8409-8134)
Institutions
- Hangzhou Normal University (CN)
- Angeles University Foundation (PH)
- Zhejiang University of Technology (CN)
- Donetsk National Technical University (UA)
Publication Details
- Journal
- Digital Health
- Published
- 2025-05-01
- DOI
- https://doi.org/10.1177/20552076251361614
- Citations
- 2
- Primary Topic
- Artificial Intelligence in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 5.88