This project aims to develop a machine learning model to predict malaria treatment failure at the patient level, enabling more personalized and effective care. We focus on artemether-lumefantrine (AL), the first-line therapy in Angola, where our clinical trial data (PACTR202405595426468) indicate suspected partial resistance. Using patient-level data, including demographic, clinical, and parasitological indicators, we are building a predictive model to support frontline decision-making. Our team is also exploring the added value of blood smear image features, annotated by expert microscopists, to improve prediction accuracy. This multidisciplinary project brings together researchers from Portugal and Angola, with international expertise in epidemiology, artificial intelligence, and malaria. It aims to enhance therapeutic strategies, inform public health policy, and strengthen cooperation with Portuguese-speaking countries.

Collaborative Institutions: CISA – Centro de Investigação em Saúde de Angola, Clínica Multiperfil, i3S – Instituto de Investigação e Inovação em Saúde, Universidade do Porto