Interpretable prediction of neonatal mortality and its key predictors using machine learning and SHAP analysis.
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| Title: | Interpretable prediction of neonatal mortality and its key predictors using machine learning and SHAP analysis. |
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| Authors: | Bitew KG; Faculty of Computing, Bahir Dar Institute of Technology, Bahir Dar University, P.O. Box 26, Bahir Dar, Ethiopia. kerebih_getinet@dmu.edu.et.; Department of Computer Science, Debre Markos University, Debre Markos, Ethiopia. kerebih_getinet@dmu.edu.et., Assabie Y; Department of Computer Science, College of Natural and Computational Sciences, Addis Ababa University, Addis Ababa, Ethiopia., Tegegne T; Faculty of Computing, Bahir Dar Institute of Technology, Bahir Dar University, P.O. Box 26, Bahir Dar, Ethiopia. |
| Source: | BMC medical informatics and decision making [BMC Med Inform Decis Mak] 2026 May 21; Vol. 26 (1). Date of Electronic Publication: 2026 May 21. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: BioMed Central Country of Publication: England NLM ID: 101088682 Publication Model: Electronic Cited Medium: Internet ISSN: 1472-6947 (Electronic) Linking ISSN: 14726947 NLM ISO Abbreviation: BMC Med Inform Decis Mak Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
| ISSN: | 1472-6947 |
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| DOI: | 10.1186/s12911-026-03567-1 |
