Research Projects

The government and health organizations aim to build a fortified healthy society, but progress has been slow due to communicable diseases like malaria and tuberculosis. The novel corona (COVID-19) virus has further accelerated this issue, with nearly 200 countries at risk of the disease from 2019 onwards. The World Health Organization (WHO) emphasizes the importance of communicable disease alert and response for mass gatherings. This project aims to design a web and mobile-based prediction and response system using deep learning algorithms to predict, track, visualize, prevent, and treat outbreaks of communicable diseases in real-time. This enables health organizations to focus on vulnerable groups like children, senior citizens, and pregnant women. The project addresses the gap between data science and healthcare computing by bringing together the domains of data science, machine learning, and computing for long-term benefits in health data analysis. The objectives are grouped into two broad classes: back-end for data acquisition phase and front-end for disease prediction, track, visualize with a geo-tag, and dissemination system. The back-end side aims to implement a fast and scalable deep learning algorithm to ingest and pre-process communicable diseases data, design and develop a computational framework with post-processing and statistical analysis tools, and design and develop a prototype framework for generating information from processed data using the latest data visualization tools.