Background: Human immunodeficiency virus (HIV) remains a major public health challenge in sub-Saharan Africa, where linguistic diversity and limited digital health resources constrain patient education and antiretroviral therapy (ART) adherence. Amharic, one of Africa’s most widely spoken languages, remains underrepres...
B. Dejene, Yaregal Assabie, Mulugeta Tadele et al.· Technologies· 0 citations
Although AI models demonstrate promising predictive performance, their clinical applicability is limited by substantial methodological limitations, including high risk of bias, inadequate validation, poor calibration and limited transparency.
B. Dejene, Yaregal Assabie, Mulugeta Tadele et al.· HIV Medicine· 0 citations
A fine-tuned AfroXLMR model demonstrates promising performance in Amharic multi-label emotion classification by fine-tuning AfroXLMR by integrating explainable artificial intelligence (XAI) into the framework.
Yeshimebet Bayu, Demeke Endalie, T. Tegegne· Scientific Reports· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.