Early gestational diabetes mellitus risk predictor using neural network with NearMiss
In this study, we proposed an innovative interpretable early GDM risk prediction model based on MLP. This model is designed to offer assistance in estimating the risk of GDM in early pregnancy, enabling proactive prevention and timely intervention.
Authors
- Xiaojie Su (ORCID: https://orcid.org/0000-0002-9623-3102)
- Min Zhao (ORCID: https://orcid.org/0000-0002-7442-1655)
- Lihong Huang (ORCID: https://orcid.org/0000-0001-8691-5532)
Institutions
- First Affiliated Hospital of Xiamen University (CN)
Publication Details
- Journal
- Gynecological Endocrinology
- Published
- 2025-02-24
- DOI
- https://doi.org/10.1080/09513590.2025.2470317
- Citations
- 5
- Primary Topic
- Gestational Diabetes Research and Management
- Type
- article
- Field-Weighted Citation Impact
- 10.29
Funders
- Natural Science Foundation of Fujian Province