Med-MGF: multi-level graph-based framework for handling medical data imbalance and representation
When compared to all baseline models, MedMGF achieved the highest SEN and AUC results, demonstrating the potential for several healthcare applications.
Authors
- Shu‐Ling Chong (ORCID: https://orcid.org/0000-0003-4647-0019)
- Jan Hau Lee (ORCID: https://orcid.org/0000-0002-8430-4217)
- Kim Leng Poh (ORCID: https://orcid.org/0000-0003-2974-8090)
- Tuong Minh Nguyen (ORCID: https://orcid.org/0000-0002-8809-4800)
Institutions
- National University of Singapore (SG)
- SingHealth Duke-NUS Academic Medical Centre (SG)
- KK Women's and Children's Hospital (SG)
Publication Details
- Journal
- BMC Medical Informatics and Decision Making
- Published
- 2024-09-02
- DOI
- https://doi.org/10.1186/s12911-024-02649-2
- Primary Topic
- Machine Learning in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 0.00