The aim of this paper is to describe the design and the preliminary validation of a platform developed to collect and automatically analyze biomedical signals for risk assessment of cardiovascular events in hypertensive patients. This m-health platform, based on cloud computing, was designed to be flexible, extensible, and transparent, and to provide proactive remote monitoring via data-mining functionalities. Clinical trials were designed to test the system. The data of a retrospective study were adopted to train and test the platform. The developed system was able to predict a future vascular event within the next 12 months with an accuracy rate of 67%. In an ongoing prospective trial, almost all the recruited patients accepted favorably the system with a limited rate of inadherences causing of data losses (<20%). The developed platform supported clinical decision by processing tele-monitored data and providing quick and accurate risk assessment of cardiovascular events.
CITATION STYLE
Melillo, P., Scala, P., Crispino, F., & Pecchia, L. (2014). Cloud-based remote processing and data-mining platform for automatic risk assessment in hypertensive patients. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8868, 155–162. https://doi.org/10.1007/978-3-319-13105-4_24
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