Using machine learning techniques to help improve intensive care outcomes in traumatic brain injuries

This project aims to develop a real time application for prediction of intensive care outcomes in traumatic brain injuries. It utilises heart rate variability parameters, applies ECG signal analysis techniques in combination with machine learning and feature selection algorithms. The candidate will investigate time series analysis and various classification methodologies, and will develop a software pipeline from data collection to prediction model. Experience in computer programming (eg. Python) is required. Basic knowledge in statistics, time series signal analysis, artificial neural network and genetic algorithm are preferred.