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Predicting early infant diagnosis (EID) results for HIV exposed infants in a resource-limited setting using machine learning models: evidence from Amhara Public Health Institute data (2024/2025)

Crossref DOI link: https://doi.org/10.1186/s12879-025-12508-8

Published Online: 2026-01-06

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Melese, Zelalem Yitayal

Takilo, Mitiku Kassaw

Mengistu, Abraham Keffale

Shimie, Aynadis Worku

Teferi, Gizaw Hailiye

Anteneh, Ashagrie

Ayalew, Wubete Lule

Tizie, Sefefe Birhanu

Mengistie, Muluken Belachew
License Information

Text and Data Mining valid from 2026-01-06

Version of Record valid from 2026-02-04
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Article History

Received: 18 October 2025

Accepted: 31 December 2025

First Online: 6 January 2026

Declarations

:

: The dataset was collected after securing all required legal permissions from the responsible organizations. Ethical approval was granted by the Ethical Review Committee of the College of Medicine and Health Sciences, Debre Markos University (Reference number: RCSTTD/442/01/17). Additional permission was obtained from the Amhara Public Health Institute. Informed consent was obtained from all participants, and we confirm that this research complies with the principles of the Declaration of Helsinki.

: The consent for publication is not applicable in this study.

: The authors declare no competing interests.

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