Project Abstract

The project explores the merging of healthcare and technology, focusing on the utilisation of the National Health and Nutrition Examination Survey (NHANES) dataset for pattern discovery and visualisation. NHANES, a comprehensive dataset encompassing demographic, socioeconomic, dietary, and health-related information, offers valuable insights into public health trends. However, its vastness and complexity pose challenges for efficient analysis and interpretation. The research aims to address these challenges by enhancing the NVisualiser web application developed by Toby E. Rea. This involves improving data handling, visualisation capabilities, and user interface to facilitate deeper insights into the dataset. The dissertation researches the broader context of data science in healthcare, emphasising the role of big data analytics and data visualisation in disease prediction, outbreak detection, and improving public health. It reviews existing literature, initiatives, and methodologies, highlighting gaps and opportunities for further research and development.By enhancing the NVisualiser application and utilising advanced data visualisation techniques, The project aims to give users and researchers the tools they need to analyse data better and make informed decisions. Through careful evaluation and improvement, it seeks to make healthcare data analysis and visualisation easier and more effective.

Keywords: Machine Learning, Data Visualisation, Big Data

 Conference Details

Session: Poster Session A at Poster Stand 28

Location: Sir Stanley Clarke Auditorium at Tuesday 7th 13:30 – 17:00

Markers: Benjamin Mora, Fernando Maestre Avila

Course: BSc Computer Science, 3rd Year

Future Plans: Other