Gedefaw, Andualem Enyew
Mengistu, Abraham Keffale
Maru, Tadele Chekol
Walle, Agmasie Damtew
Alemayehu, Meron Asmamaw
Yehuala, Tirualem Zeleke
Baykemagn, Nebebe Demis
Article History
Received: 30 December 2024
Accepted: 24 July 2025
First Online: 30 September 2025
Declarations
:
: The study participants gave their informed consent after the study protocol was evaluated and approved by Debre Markos University’s ethical review board. The Amhara Regional Public Health Institute provided a letter of permission (Reference No: APHI/D/M/306/007). Due to the retrospective nature of the study, informed consent was not used. However, the confidentiality of the data was supported by keeping the extracted information private and by ensuring that it could not be used for any purpose other than study-related purposes. Only the study was conducted using the data retrieved. As a result, the data-gathering tool did not hold participants’ names or any other personal information about them. ML deployment in HIV care requires balancing utility with privacy. While this study used de-identified data, future implementations must ensure informed consent and transparency in how predictions are generated. We propose collaborative frameworks with local ethics boards to govern ML use in sensitive populations. Future ML implementations should integrate informed consent for predictive model use, ensure transparency via explainable AI (e.g., SHAP), and adhere to local data privacy laws (e.g., anonymization, opt-out options). Collaborative frameworks with ethics boards are critical for scaling. We recommend developing ethical frameworks in collaboration with local IRBs to guide the responsible deployment of ML in HIV care, ensuring fairness, privacy, and patient autonomy. The study adhered to the Helsinki Declaration.
: Not applicable.
: The authors declare no competing interests.