Abstract
Advances in medical care and computer technology in recent decades have expanded the parameters of the traditional domain of medical services. This scenario has created new opportunities for building applications to provide enterprise services in an efficient, diverse and highly dynamic environment.
Moreover the IoT revolution is redesigning modern health care with promising technological prospect and has made IT-based healthcare systems expensive, competitive and complex. Their complexity is also enhanced by the use of semantic models which allow the detection and prediction of a patient health anomalies and the therapy management is produced accordingly.
In this paper will be presented a prototypical framework that, starting from the stream analysis and processing coming from wearable devices, tries to detect the possible health anomalies in real time and, through a heuristic and ontology-driven approach capable of reasoning on the patient’s conditions, it gives hints about possible diseases that are currently going on.
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Di Martino, B., Esposito, A., Liguori, S., Ospedale, F., Maisto, S.A., Nacchia, S. (2018). A Fuzzy Prolog and Ontology Driven Framework for Medical Diagnosis Using IoT Devices. In: Barolli, L., Terzo, O. (eds) Complex, Intelligent, and Software Intensive Systems. CISIS 2017. Advances in Intelligent Systems and Computing, vol 611. Springer, Cham. https://doi.org/10.1007/978-3-319-61566-0_83
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DOI: https://doi.org/10.1007/978-3-319-61566-0_83
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