Kenyan Neonatal Mortality Risk Predictor: A User-Centred Design Evaluation (Preprint)
The study is expected to generate actionable evidence to support the translation of ML-based neonatal risk prediction into routine clinical practice in LMIC settings, thereby reducing neonatal mortality and advancing progress toward Sustainable Development Goal target 3.2.
Authors
- Danny Ronald Nyatuka (ORCID: https://orcid.org/0000-0001-6251-7695)
- Betsy Muriithi (ORCID: https://orcid.org/0000-0003-1393-2045)
- Md Shafiqur Rahman Jabin (ORCID: https://orcid.org/0000-0003-0197-8716)
- Faith Siva (ORCID: https://orcid.org/0000-0003-0608-0892)
- Esther Kakhata
- Paul Macharia
Institutions
- University of Bradford (GB)
- Strathmore University (KE)
- Linnaeus University (SE)
Publication Details
- Journal
- JMIR Research Protocols
- Published
- 2025-08-27
- DOI
- https://doi.org/10.2196/81996
- Primary Topic
- Global Maternal and Child Health
- Type
- article
- Field-Weighted Citation Impact
- 0.00