Yogyakarta, June 23, 2025 — How can artificial intelligence help respond to infectious disease outbreaks? This question became the starting point of the AI for Infectious Disease Modeling (AI for IDM) Track session held on the first day of an intensive training series in epidemiology and public health.
Led by experts from MDRU, including Thitiya Theparod and Myat Su Ming, the session guided participants in exploring the potential of AI within the contexts of epidemiology, tropical medicine, and health policy. The material focused on practical skills for processing various types of epidemiological data, such as text, images, and audio, as well as building predictive and diagnostic systems based on machine learning and deep learning.
Through hands-on practice using Orange and supporting Python scripts, participants learned how to create classification models, regression models, and disease risk detection models. Beyond technical focus, the session emphasized the importance of ethical approaches in AI implementation, including introducing citizen science methods as part of public participation in health data collection and utilization.
With a step-by-step approach, starting from basic algorithms to complex architectures, participants are encouraged to not only understand how AI works but also the context of its responsible use. The hope is that this session will equip participants with the analytical and critical thinking skills needed to address the challenges of infectious diseases today and in the future.
Keywords: MIDSEA, Modelling, Infectious Disease Modelling
Author: Iin Nauli Rahmawati
Photo: Lucetta Amarakamini