Intelligent Early Warning and Response System Based on Health System Routin Data and Environment Data to Improve National Health Resilience.

Overview

This project leverages AI to predict and respond to dengue outbreaks by collecting data on mosquito populations, rainfall, weather conditions, and reports from online medical consultations. AI algorithms analyze these patterns to learn from past outbreaks and generate accurate predictions, supporting early warning and targeted response efforts.

The system empowers communities to prepare for potential dengue outbreaks by providing timely alerts and actionable guidance. It also strengthens healthcare facilities’ ability to collect, manage, and interpret disease-related data. By using large language models (LLMs) to read and summarize electronic medical records, the system enables faster, more informed decision-making for public health authorities and practitioners.

Responsible AI Practices

The project is developed in close collaboration with the Ministry of Health of Indonesia, ensuring that AI solutions are contextually relevant, address local health challenges, and align with national health priorities. This partnership promotes responsible, ethical, and effective deployment of AI in the healthcare system.