Title: Intelligent medical record management: a diagnosis support system

Authors: Flora Amato; Giovanni Cozzolino; Antonino Mazzeo; Sara Romano

Addresses: DIETI – Department of Electrical Engineering and Information Technology, University of Naples 'Federico II', Italy ' DIETI – Department of Electrical Engineering and Information Technology, University of Naples 'Federico II', Italy ' DIETI – Department of Electrical Engineering and Information Technology, University of Naples 'Federico II', Italy ' Centro Regionale Information Communication Technology – CeRICT scrl, Complesso Universitario di Monte Sant'Angelo, Naples, Italy

Abstract: The increasing life expectations and low birth rates radically changed the demographic structure of the European Union. The number of elderly people is growing up as well as the number of chronic diseases: this implies higher and higher healthcare costs, a reduction of healthcare personnel and requests for better care services. E-health has led to a growth of the health organisation, providing innovative and not-intrusive systems together with value-added services to the healthcare actors that contribute to enhance the efficiency and reduce the costs of complex informative systems. Many research efforts lead to innovative and not-intrusive e-health systems. In this work, we present a system for supporting medical decisions. It is based on semantic analysis of available medical data. The system implements an innovative methodology, which combines different semantic approaches in order to extract the representation of a given document expressed in natural language, and to associate it to a set of RDF triples.

Keywords: e-health; knowledge management; data integration; natural language processing; decision support system.

DOI: 10.1504/IJHPCN.2018.096726

International Journal of High Performance Computing and Networking, 2018 Vol.12 No.4, pp.391 - 399

Received: 04 Jul 2016
Accepted: 12 Feb 2017
Published online: 10 Dec 2018 *

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