Transforming Chinese cohort studies through artificial intelligence: a new era of population health research
<b>Tien Yin Wong and colleagues</b> explore how artificial intelligence can tackle persistent challenges in Chinese epidemiological studies and analyse the regulatory frameworks and barriers to implementation that must be overcome to ensure equitable, scientifically rigorous population health research
Authors
- Huating Li (ORCID: https://orcid.org/0000-0003-0526-5545)
- Josip Car (ORCID: https://orcid.org/0000-0001-8969-371X)
- Tien Yin Wong (ORCID: https://orcid.org/0000-0002-8448-1264)
- Yih Chung Tham (ORCID: https://orcid.org/0000-0002-6752-797X)
- Dian Zeng
Institutions
- National University of Singapore (SG)
- Shanghai Jiao Tong University (CN)
- King's College London (GB)
- Singapore National Eye Center (SG)
- Singapore Eye Research Institute (SG)
- Duke-NUS Medical School (SG)
- Shanghai Sixth People's Hospital (CN)
- Beijing Tsinghua Chang Gung Hospital (CN)
- Tsinghua University (CN)
Publication Details
- Journal
- BMJ
- Published
- 2025-10-23
- DOI
- https://doi.org/10.1136/bmj-2024-082568
- Citations
- 3
- Primary Topic
- Health, Environment, Cognitive Aging
- Type
- article
- Field-Weighted Citation Impact
- 3.60