Is explainable AI ready for digital health?

• Main Author: Chia, Charlene Si Yin
• Other Authors: Fan Xiuyi
• Format: Final Year Project
• Language: English
• Published: Nanyang Technological University 2024
• Subjects: Computer and Information Science
• Online Access: https://hdl.handle.net/10356/175208
• Institution: Nanyang Technological University

Explainable Artificial Intelligence (XAI) is a set of techniques that allows human users to understand the reasoning and logic behind machine learning algorithms. This project addresses the validity and accuracy of XAI methods in Digital Health. Given a real-life dataset of certain eye conditions and the expected time for the next appointment, this study aims to use machine learning and XAI methods to predict the time taken for the next appointment and the diagnosis of eye conditions. A set of guidelines by the Singapore National Eye Centre (SNEC) and the Singapore Integrated Diabetic Retinopathy Programme (SiDRP), will be used to evaluate the accuracy and validity of the XAI explanations.