Predicting dengue transmission rates by comparing different machine learning models with vector indices and meteorological data

• Main Authors: Ong, Song Quan, Pradeep Isawasan, Ahmad Mohiddin Mohd Ngesom, Hanipah Shahar, As’malia Md Lasim, Gomesh Nair
• Format: Article
• Language: English; English
• Published: Springer Nature 2023
• Subjects: QR355-502 Virology; RC109-216 Infectious and parasitic diseases
• Online Access: https://eprints.ums.edu.my/id/eprint/38089/1/ABSTRACT.pdf; https://eprints.ums.edu.my/id/eprint/38089/2/FULL%20TEXT.pdf; https://eprints.ums.edu.my/id/eprint/38089/; https://doi.org/10.1038/s41598-023-46342-2
• Institution: Universiti Malaysia Sabah

Machine learning algorithms (ML) are receiving a lot of attention in the development of predictive models for monitoring dengue transmission rates. Previous work has focused only on specific weather variables and algorithms, and there is still a need for a model that uses more variables and algorith...