Health AI Central
Peer-Reviewed Publication
Health Data Sci2025;50321.January 1, 2025Journal Article

Bridging Data Gaps in Healthcare: A Scoping Review of Transfer Learning in Structured Data Analysis.

Siqi Li1, Xin Li1, Kunyu Yu1, Qiming Wu1, Di Miao1, Mingcheng Zhu1, Mengying Yan2, Yuhe Ke3, Danny D'Agostino1, Yilin Ning1, Ziwen Wang1, Yuqing Shang1, Molei Liu4,5,6, Chuan Hong2, Nan Liu1,7,8
1Centre for Quantitative Medicine, Duke-NUS Medical School, Singapore, Singapore.
2Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA.
3Department of Anesthesiology, Singapore General Hospital, Singapore, Singapore.
4Department of Biostatistics, Columbia University Mailman School of Public Health, New York, NY, USA.
5Department of Biostatistics, Peking University Health Science Center, Peking University, Beijing, China.
6Beijing International Center for Mathematical Research, Peking University, Beijing, China.
7Programme in Health Services and Systems Research, Duke-NUS Medical School, Singapore, Singapore.
8Institute of Data Science, National University of Singapore, Singapore, Singapore.
PubMed PMC DOI PDF

Abstract

Background: Clinical and biomedical research in low-resource settings often faces substantial challenges due to the need for high-quality data with sufficient sample sizes to construct effective models. These constraints hinder robust model training and prompt researchers to seek methods for leveraging existing knowledge from related studies to support new research efforts. Transfer learning (TL),…

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