Dr. James Ng

Summary

The project involves applying state-of-the-art approaches, including statistical modelling and Artificial Intelligence techniques to analyse data, to investigate risk factors contributing to depression and anxiety, and the dietary and lifestyle changes that should be implemented to help to improve mental health in older people.

Funding Agency

Higher Education Authority

Programme

North-South Research Programme

Summary

This project aims to develop a robust, evidence-based standardised predictive model to predict ANCA-Associated Vasculitis (AAV) flare risk. Our approach uses semantic web technology to integrate standardised clinical data derived from a longitudinal inception cohort, physician clinical assessment, focused biomarker analysis and app-based patient feedback. The focus of this project is the development of novel Association Rule Mining based predictive models suitable for the complex longitudinal nature of the data and to embed the resulting algorithms alongside international standards development such as ISO/IEC JTC 1/SC 42 for Artificial Intelligence. Unlike many black box data mining and machine learning methods, humans can easily understand the decision-making process of ARM models. The interpretability of ARM based tools makes them particularly suitable to be deployed in a wide range of clinical environments by aligning them with international standards for health applications. The benefit of the project is potentially significant healthcare costs in chronic inflammatory and autoimmune diseases can be expected to drop, while patient/carer burden, clinical time and resources will all be reduced.

Funding Agency

Horizon 2020 Marie Sklodowska-Curie COFUND

Programme

ELITE-S Programme