AI for healthcare

• Main Author: Hu, Rickson Hong Rui
• Other Authors: Erik Cambria
• Format: Final Year Project
• Language: English
• Published: Nanyang Technological University 2022
• Subjects: Engineering::Computer science and engineering
• Online Access: https://hdl.handle.net/10356/156395
• Institution: Nanyang Technological University

In today’s world, the number of people with health conditions are growing at an alarming rate. This phenomenon is a consequence of various factors such as unhealthy lifestyle and genetics. One condition that has constantly been a major cause for concern is heart disease, which unfortunately has become more common and puts the lives of many at risk. Even though there are cases where heart disease is asymptomatic and go undetected in some patients, it can mostly be identified using a few major risk factors. With the current rapid advancements in technology, machine learning and artificial intelligence could potentially offer a solution to this medical crisis. This project focuses on using different machine learning classification techniques to predict the likelihood of individuals having heart disease based on various medical data. The techniques include Neural Network, Logistic Regression, Naïve Bayes, Support Vector Machine, K-Nearest Neighbours, Decision Tree, Random Forest, Boosting and Stacking Ensemble Learning. Their performances are compared against one another in order to determine which is the best model that is capable of producing the most accurate prediction.