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Knowledge-Based Decision Support in Healthcare via Near Field Communication.
Loseto, Giuseppe; Scioscia, Floriano; Ruta, Michele; Gramegna, Filippo; Ieva, Saverio; Pinto, Agnese; Scioscia, Crescenzio.
Afiliação
  • Loseto G; Department of Electrical and Information Engineering (DEI), Polytechnic University of Bari, via E. Orabona 4, 70125 Bari, Italy.
  • Scioscia F; Department of Electrical and Information Engineering (DEI), Polytechnic University of Bari, via E. Orabona 4, 70125 Bari, Italy.
  • Ruta M; Department of Electrical and Information Engineering (DEI), Polytechnic University of Bari, via E. Orabona 4, 70125 Bari, Italy.
  • Gramegna F; Department of Electrical and Information Engineering (DEI), Polytechnic University of Bari, via E. Orabona 4, 70125 Bari, Italy.
  • Ieva S; Department of Electrical and Information Engineering (DEI), Polytechnic University of Bari, via E. Orabona 4, 70125 Bari, Italy.
  • Pinto A; Department of Electrical and Information Engineering (DEI), Polytechnic University of Bari, via E. Orabona 4, 70125 Bari, Italy.
  • Scioscia C; Department of Emergency and Organ Transplantation (DETO) Rheumatology Unit, University of Bari, Piazza G. Cesare 11, 70124 Bari, Italy.
Sensors (Basel) ; 20(17)2020 Aug 31.
Article em En | MEDLINE | ID: mdl-32878204
The benefits of automatic identification technologies in healthcare have been largely recognized. Nevertheless, unlocking their potential to support the most knowledge-intensive medical tasks requires to go beyond mere item identification. This paper presents an innovative Decision Support System (DSS), based on a semantic enhancement of Near Field Communication (NFC) standard. Annotated descriptions of medications and patient's case history are stored in NFC transponders and used to help caregivers providing the right therapy. The proposed framework includes a lightweight reasoning engine to infer possible incompatibilities in treatment, suggesting substitute therapies. A working prototype is presented in a rheumatology case study and preliminary performance tests are reported. The approach is independent from back-end infrastructures. The proposed DSS framework is validated in a limited but realistic case study, and performance evaluation of the prototype supports its practical feasibility. Automated reasoning on knowledge fragments extracted via NFC enables effective decision support not only in hospital centers, but also in pervasive IoT-based healthcare contexts such as first aid, ambulance transport, rehabilitation facilities and home care.
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Texto completo: 1 Eixos temáticos: Difusao_do_conhecimento_cientifico Base de dados: MEDLINE Assunto principal: Técnicas de Apoio para a Decisão / Bases de Conhecimento / Serviços de Assistência Domiciliar Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Eixos temáticos: Difusao_do_conhecimento_cientifico Base de dados: MEDLINE Assunto principal: Técnicas de Apoio para a Decisão / Bases de Conhecimento / Serviços de Assistência Domiciliar Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article