Supervisor
Muhammad Iqbal
Programme
BSc (Hons) in Computing in IT
Abstract
This project presents an innovative health tracking and disease prevention application designed for the healthcare sector. The application enables users to log daily meals, exercise routines, and lifestyle habits, providing a holistic overview of their health status. Leveraging Machine Learning and data analytics, the solution delivers personalised insights and predictive analytics, empowering users to manage their well-being proactively.
The application offers detailed data analysis to identify potential disease risks, allowing users to make informed decisions about their health. The report discusses the development process, the implementation of machine learning models, and data visualisation techniques. It highlights the transformative impact of this technology in promoting proactive health management and improving overall user engagement in preventive care.
This project underscores the potential of ML-driven applications to revolutionise health tracking and risk prevention, bridging the gap between technology and healthcare for better outcomes.
Date of Award
2024
Full Publication Date
2024
Access Rights
open access
Document Type
Undergraduate Project
Resource Type
bachelor thesis
Recommended Citation
Cavalcanti Albuquerque Brayner, Luiza and Pacheco, Edgard, "Using Predictive Analytics to identify risk of Heart Disease based on lifestyle factors and health metrics." (2024). ICT. 71.
https://arc.cct.ie/ict/71