SmartHeart: A Cloud and Machine Learning Framework for Early Cardiovascular Disease Prediction

Cardiovascular diseases (CVDs) are emerging as a big problem in the world today and thus the necessity to develop new methods of early prediction and prevention. The present paper presents SmartHeart a cloud-based system that outputs the risk of cardiovascular diseases in patients based on their machine learning and predictive features. The framework is a combination of real-time data collection of multiple sources such as wearable devices, electronic health records, and lifestyle factors to process the patient health data on the cloud. SmartHeart will coupled with modern machine learning algorithms allow achieving the most complete cardiovascular risk assessment and pre-detection of possible cardiovascular problems, which will help to provide timely interventions and individually tailored care. The scalability of the system and the fact that it uses cloud implementation allows efficient storage and processing of huge volumes of data and ensuring data privacy and security. Their robustness and generalizability on various populations are increased when the predictive models are trained on different datasets. In addition, SmartHeart shall have simple interfaces to both medical practitioners and patients so that they easily access their data and have actionable information. This paper presents an overview of the architecture, machine learning techniques, and evaluation of the framework that can be considered as absolutely transformational in the field of cardiovascular disease prediction and improving the overall healthcare outcomes and reducing popular strains on the healthcare system all over the world.