Machine and deep learning approaches for monitoring predictive in healthcare

This work focuses on the analysis and development of data analytics and machine learning models in healthcare. Specifically, an overview is given of the state of the art regarding the challenges and opportunities of using big data analytics, machine learning and sensor technologies in healthcare. The different sources of healthcare data and their possible applications are investigated, focusing on the analysis of data relating to patients with heart attacks. This is the leading cause of death in the world today. The aim is to identify possible correlations and patterns in the analysis values of heart attack patients compared to healthy patients in order to highlight possible emerging differences. In addition, supervised machine learning models are trained to classify those at risk of heart attack versus those not at risk, and then identify the best model that achieves the highest accuracy.