Title
Remote Health Monitoring of Heart Failure With Data Mining via CART Method on HRV Features
Abstract
Disease management programs, which use no advanced information and computer technology, are as effective as telemedicine but more efficient because less costly. We proposed a platform to enhance effectiveness and efficiency of home monitoring using data mining for early detection of any worsening in patient's condition. These worsenings could require more complex and expensive care if not recognized. In this letter, we briefly describe the remote health monitoring platform we designed and realized, which supports heart failure (HF) severity assessment offering functions of data mining based on the classification and regression tree method. The system developed achieved accuracy and a precision of 96.39% and 100.00% in detecting HF and of 79.31% and 82.35% in distinguishing severe versus mild HF, respectively. These preliminary results were achieved on public databases of signals to improve their reproducibility. Clinical trials involving local patients are still running and will require longer experimentation.
Year
DOI
Venue
2011
10.1109/TBME.2010.2092776
Biomedical Engineering, IEEE Transactions
Keywords
Field
DocType
classification,data mining,diseases,electrocardiography,medical signal processing,patient monitoring,regression analysis,trees (mathematics),CART method,HRV features,classification,data mining,disease management programs,heart failure,patient condition,public databases,regression tree method,remote health monitoring,Classification and regression tree (CART),data mining (DM),heart failure (HF),heart rate variability (HRV),home monitoring (HM)
Telemedicine,Decision tree,Data mining,Heart failure,Data processing,Computer science,Heart rate variability,Remote patient monitoring,Clinical trial,Computer technology
Journal
Volume
Issue
ISSN
58
3
0018-9294
Citations 
PageRank 
References 
26
1.86
7
Authors
3
Name
Order
Citations
PageRank
Leandro Pecchia119215.66
Paolo Melillo216711.65
Marcello Bracale31039.53