AI Medical Compendium Journal:
Parasitology research

Showing 1 to 4 of 4 articles

Epidemiology and risk factors of Clonorchis sinensis infection in the mountainous areas of Longsheng County, Guangxi: insights from automated machine learning.

Parasitology research
Clonorchis sinensis (C. sinensis) is mainly prevalent in Northeast and South China, with Guangxi being the most severely affected region. This study aimed to evaluate the prevalence and identify the risk factors of C. sinensis infection in Longsheng ...

Prediction on the spatial distribution of the seropositive rate of schistosomiasis in Hunan Province, China: a machine learning model integrated with the Kriging method.

Parasitology research
Schistosomiasis remains a formidable challenge to global public health. This study aims to predict the spatial distribution of schistosomiasis seropositive rates in Hunan Province, pinpointing high-risk transmission areas and advocating for tailored ...

Artificial intelligence (AI): a new window to revamp the vector-borne disease control.

Parasitology research
Artificial intelligence (AI) facilitates scientists to devise intelligent machines that work and behave like humans to resolve difficulties and problems by utilizing minimal resources. The Healthcare sector has benefited due to this. Mosquito-transmi...

Application of kNN and SVM to predict the prognosis of advanced schistosomiasis.

Parasitology research
Predictive models for prognosis of small sample advanced schistosomiasis patients have not been well studied. We aimed to construct prognostic predictive models of small sample advanced schistosomiasis patients using two machine learning algorithms, ...