Patient-level performance evaluation of a smartphone-based malaria diagnostic application - Yu, H; Mohammed, FO; Abdel Hamid, M; Yang, F; Kassim, YM; Mohamed, AO; Maude, RJ; Ding, XC; Owusu, EDA; Yerlikaya, S; Dittrich, S; Jaeger, S (BioMed Central, 2023)
Background Microscopic examination is commonly used for malaria diagnosis in the field. However, the lack of well-trained microscopists in malaria-endemic areas impacted the most by the disease is a severe problem. Besides, the examination process is time-consuming and prone to human error. Automated diagnostic systems based on machine learning offer great potential to overcome these problems. This study aims to evaluate Malaria Screener, a smartphone-based application for malaria diagnosis.