Engineering Commons^™

Predictive Analytics In Cardiac Healthcare And 5g Cellular Networks, Dilranjan S. Wickramasuriya

USF Tampa Graduate Theses and Dissertations

This thesis proposes the use of Machine Learning (ML) to two very distinct, yet compelling, applications – predicting cardiac arrhythmia episodes and predicting base station association in 5G networks comprising of virtual cells. In the first scenario, Support Vector Machines (SVMs) are used to classify features extracted from electrocardiogram (EKG) signals. The second problem requires a different formulation departing from traditional ML classification where the objective is to partition feature space into constituent class regions. Instead, the intention here is to identify temporal patterns in unequal-length sequences. Using Recurrent Neural Networks (RNNs), it is demonstrated that accurate predictions can be …