H2HCare paper submitted to 2023 IEEE 19th International Conference on Intelligent Computer Communication and Processing (ICCP 2023), to be held October 26-28, 2023 in Cluj-Napoca, Romania:
Title: A Machine Learning based Platform for Remote Management of Heart Failure Patients
Abstract: Heart failure is a growing concern due to its high incidence nowadays, also representing a major cause of morbidity and mortality worldwide. In this paper we propose a web-based platform that incorporates both the clinical data prediction aspect and the continuous monitoring of the heart health. We implement multiple machine learning models that can support the doctors in the process of classification between a healthy and unhealthy situation. The platform benefits from an ETL (Extract, Transform, Load) sub-system that processes biometric data from smart wearables and displays it in customizable dashboards for a more illustrative visualization. The prediction service integrates three Machine Learning (ML) techniques, namely Logistic Regression, Naïve Bayes Classifier, and a custom Artificial Neural Network responsible for making classifications on the monitored data. The results illustrate that the proposed solution’s usage for performing remote monitoring and heart health assessment is feasible, obtaining promising accuracies with the aid of a public heart failure dataset (best accuracy of 88.5%).