A machine learning system to improve heart failure patient assistance

IEEE Journal of Biomedical and Health Informatics

Volumn 18, Issue 6, 2014, Pages 1750-1756

  Guidi, Gabriele ^a   Pettenati, Maria Chiara ^b   Melillo, Paolo ^c,d   Iadanza, Ernesto ^a  

^a UNIVERSITY OF FLORENCE   (Italy)

^b ICON (International Center of Computational Neurophotonics) Foundation   (Italy)

^c UNIVERSITY OF BOLOGNA   (Italy)

^d SECOND UNIVERSITY OF NAPLES   (Italy)

Author keywords

Heart failure (HF); Machine learning; Telemonitoring

Indexed keywords

CARDIOLOGY; CLASSIFICATION (OF INFORMATION); DATABASE SYSTEMS; DECISION SUPPORT SYSTEMS; DECISION TREES; FAILURE (MECHANICAL); FUNCTION EVALUATION; FUZZY INFERENCE; PETROLEUM RESERVOIR EVALUATION; RANDOM FORESTS; SUPPORT VECTOR MACHINES; SUPPORT VECTOR REGRESSION; TELEMEDICINE;

CLASSIFICATION AND REGRESSION TREE; CLINICAL DECISION SUPPORT SYSTEMS; HEART FAILURE; INTELLIGENT FUNCTIONS; MACHINE LEARNING APPROACHES; MANAGEMENT INTERFACES; RANDOM FOREST ALGORITHM; TELE-MONITORING;

LEARNING SYSTEMS;

BRAIN NATRIURETIC PEPTIDE;

ALGORITHM; ARTIFICIAL INTELLIGENCE; DECISION SUPPORT SYSTEM; FUZZY LOGIC; HEART FAILURE; HEART STROKE VOLUME; HUMAN; PATHOPHYSIOLOGY; PROCEDURES; REPRODUCIBILITY; TELEMEDICINE;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; DECISION SUPPORT SYSTEMS, CLINICAL; FUZZY LOGIC; HEART FAILURE; HUMANS; NATRIURETIC PEPTIDE, BRAIN; REPRODUCIBILITY OF RESULTS; STROKE VOLUME; TELEMEDICINE;

EID: 84909634152     PISSN: 21682194     EISSN: 21682208     Source Type: Journal    
DOI: 10.1109/JBHI.2014.2337752     Document Type: Article

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