Borne Disease

Borne diseases, illnesses transmitted by vectors like mosquitoes and ticks, pose significant global health challenges. Current research focuses on improving disease surveillance and prediction using machine learning techniques, such as recurrent neural networks, convolutional neural networks, and agent-based models coupled with graph neural networks, to analyze diverse data sources including remote sensing imagery, clinical records, and climate data. These advancements aim to enhance early warning systems, optimize resource allocation for disease control, and ultimately reduce the burden of borne diseases, particularly in vulnerable populations. The development of user-friendly applications for disease identification and improved diagnostic tools using ontologies and semantic web technologies also represent key areas of progress.