Case 2- Ai for Disease Surveillance
Ai-Based Disease Surveillance and Outbreak Alert System
Infectious disease surveillance is an emerging field that studies data collection, data sharing, data modelling, and data management issues in the domain of infectious diseases. This project provides an overview with specific emphasis on:
- Develop data mining, and machine learning algorithms to make accurate predictions on disease outbreaks.
- Design and development of an infectious disease information software platform.
Case studies involving real-word applications and research prototypes are presented to illustrate the application context and relevant data modelling and system design issues.
The Scope
- Develop a web-based software platform to monitor worldwide disease outbreaks and generate alerts.
- Describe epidemiologically relevant patterns of disease,
- Forecast and visualize an epidemic’s likely evolution,
- Guide the selection and evaluation of epidemic control measures and provide real-time alerts to people worldwide through email.