Physiological time series analysis using deep learning techniques

This thesis investigates the challenges of using deep learning (DL), an advanced AI technique, in physiological time series data in terms of DL models' lack of generalisability, limited training data and lack of decision-making interpretability. It proposed interpretable model design and optimisation methods, and data augmentation techniques as solutions.