[Application of machine learning models in schistosomiasis control: a review].

Abstract

Schistosomiasis is a major public health concern in the world, and precision control is crucial to combating this disease. Due to the complex and diverse transmission route of schistosomiasis, conventional statistical models have significant limitations for precision control of schistosomiasis. As an important branch of artificial intelligence, machine learning has shown remarkable advantages in schistosomiasis control and research. It has been shown that machine learning is highly effective for disease prediction and risk assessment, so as to optimize the disease control strategy and resource allocation and achieve the precision control target. This review summarizes the characteristics of machine learning models and their applications in the research of intermediate host snails and schistosomiasis.