Adekunle R.I.

Investigating climatic and demographic factors as predictors for typhoid-malaria coinfection: a machine learning analysis

A framework that serves as a proof-of-concept for the prediction of typhoid-malaria coinfection using machine learning, with diagnostic testing selected as the most reliable predictor is developed and it can be concluded that the validation of the model should be done with clinical data.