F. Mlambo

Ensemble Machine Learning for Malaria Diagnosis in Resource-Limited Settings Using Clinical and Demographic Features

It is demonstrated that ML particularly ensemble models can be used to significantly improve malaria diagnosis and the integration of these models into a web-based application could provide a scalable and accessible diagnostic tool for healthcare workers in resource limited settings.