Researchers Use AI and Data Techniques to Predict Malaria Outbreaks, United Arab Emirates

A research team at Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) is working on potentially groundbreaking research in the fight against malaria. Led by Abdulmotaleb El Saddik, professor of computer vision at MBZUAI, the team is using new technology and data techniques to predict geographical areas vulnerable to the disease based on potential weather conditions, heat, and humidity. The goal is to assist doctors and health officials in Indonesia. This breakthrough is made possible with sensory data fusion, a technique that combines data from several sensors to generate a virtual representation of the world, or a digital twin. By collecting sensory data from various sources and applying machine learning and deep learning algorithms, the researchers aim to predict potential malaria outbreaks. The team is leveraging historical data and vision sensors to accurately detect the location of mosquitoes, which carry the disease. In addition to malaria, this innovative approach could be used to combat other diseases in the future, such as dengue fever. Through this project, the researchers will gain a better understanding of data usage and be able to train new models for fighting diseases. Malaria, a life-threatening disease primarily found in tropical countries, affects approximately 250 million people annually and caused 600,000 deaths in 2021 alone, according to the World Health Organisation (WHO). By harnessing the power of artificial intelligence and data analysis, this research offers hope in the battle against malaria and other similar diseases.