Heart failure analysis dashboard for patient's remote monitoring combining multiple artificial intelligence technologies.
In this paper we describe an Heart Failure analysis Dashboard that, combined with a handy device for the automatic acquisition of a set of patient's clinical parameters, allows to support telemonitoring functions. The Dashboard's intelligent core is a Computer Decision Support System designed to assist the clinical decision of non-specialist caring personnel, and it is based on three functional parts: Diagnosis, Prognosis, and Follow-up management. Four Artificial Intelligence-based techniques are compared for providing diagnosis function: a Neural Network, a Support Vector Machine, a Classification Tree and a Fuzzy Expert System whose rules are produced by a Genetic Algorithm. State of the art algorithms are used to support a score-based prognosis function. The patient's Follow-up is used to refine the diagnosis.
Department of Electronics and Telecommunications, University of Florence, Florence, Italy. gabriele.guidi@unifi.it
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D000465:Algorithms; D001185:Artificial Intelligence; D020000:Decision Support Systems, Clinical; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D006333:Heart Failure / Q000175:diagnosis*; D006801:Humans; D008991:Monitoring, Physiologic / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D017216:Telemedicine / Q000379:methods*