Multimodal feature analysis for automated neonatal jaundice assessment using machine learning
The proposed algorithm shows promise for real-world use by enabling timely, automated jaundice assessment for families, while also offering insights for future research and broader medical applications.
Authors
- Ngiap Chuan Tan (ORCID: https://orcid.org/0000-0002-5946-1149)
- Alvin Jia Hao Ngeow (ORCID: https://orcid.org/0000-0002-1767-4402)
- Lin Zou (ORCID: https://orcid.org/0000-0002-6265-6801)
- Yunfeng Liang
- Andy Wee An Ta
- Han Leong Goh
- Millie Ming Rong Goh
Institutions
- Synopsys (Switzerland) (CH)
- Singapore General Hospital (SG)
- SingHealth Polyclinics (SG)
Publication Details
- Journal
- JAMIA Open
- Published
- 2025-11-03
- DOI
- https://doi.org/10.1093/jamiaopen/ooaf165
- Primary Topic
- Neonatal Health and Biochemistry
- Type
- article
- Field-Weighted Citation Impact
- 0.00