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.
|Titolo:||Cloud-based remote processing and data-mining platform for automatic risk assessment in hypertensive patients|
|Autori interni:||MELILLO, Paolo|
|Data di pubblicazione:||2014|
|Serie:||LECTURE NOTES IN COMPUTER SCIENCE|
|Appare nelle tipologie:||2.1 Contributo in volume (Capitolo o Saggio)|