Intention to use patient portal and its predictors among patient with diabetes in Amhara region referral hospitals, Northwest Ethiopia, 2023: UTAUT-2 model.

Background: Patient portal technology is increasingly utilized in the health care system for diabetes management as a means of communication and information-sharing tools, and it has the potential to improve access, quality, and outcomes for patients with diabetes. However, its adaptation is very low, and patients' intention toward the patient portal is unknown. This study aims to fill this gap by determining the intention to use the patient portal and its predictors among patients with diabetes in Ethiopia.

Interpretable prediction of acute respiratory infection disease among under-five children in Ethiopia using ensemble machine learning and Shapley additive explanations (SHAP).

Background: Although the prevalence of childhood illnesses has significantly decreased, acute respiratory infections continue to be the leading cause of death and disease among children in low- and middle-income countries. Seven percent of children under five experienced symptoms in the two weeks preceding the Ethiopian demographic and health survey. Hence, this study aimed to identify interpretable predicting factors of acute respiratory infection disease among under-five children in Ethiopia using machine learning analysis techniques.