A review on the use of machine learning techniques in monkeypox disease prediction

Schistosomiasis transmission in Zimbabwe: Modelling based on machine learning

“…The advantage with an approach based on both available and unseen data is that predictions can be made without necessarily having to engage in enlarged sampling. Machine-learning (ML) technology ( Keshavamurthy et al., 2022 ; Mooney & Pejaver, 2018 ; Rampogu, 2023 ; Vilne et al., 2019 ) is a most useful way in this context. It involves designing and analysing algorithms that enable computers to learn automatically.…”

“…It involves designing and analysing algorithms that enable computers to learn automatically. Unlike statistical methods, in which variable relationships are explicitly defined, ML models can achieve accurate predictions more rapidly and have therefore become popular with regard to infectious diseases ( Bergquist et al., 2024 ; Lu et al, 2022 ; Rampogu, 2023 ). This approach has been used to identify high-risk areas for S. japonicum transmission ( Gong et al., 2021 ) and the parasite’s intermediate host in China Oncomelania hupensis ( Liu et al., 2023 ; Zheng et al., 2021 ).…”