Abstract : Epilepsy is one of the most common and dangerous neurological disorders, affecting millions of people around the world every year. Its symptoms are quite subtle and the transition from one phase of the disorder to another can go undetected and end to a life threatening situation, if the patient is not carefully monitored. In this paper we propose a novel health status transition model in epilepsy, as well as an implementation scheme suitable to be used in health telemonitoring systems. This model is able to monitor the patient and detect abnormalities providing a time margin for him/her to take actions and for his/her caregivers to be prepared to help and act. Based on whole model’s transitions information we created a health-caring ontology. Finally, we used Java in order to develop an appropriate decision-making telemonitoring algorithm based on the proposed model.
Lazaros Iliadis; Ilias Maglogiannis. 12th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), Sep 2016, Thessaloniki, Greece. IFIP Advances in Information and Communication Technology, AICT-475, pp.27-38, 2016, Artificial Intelligence Applications and Innovations. 〈10.1007/978-3-319-44944-9_3〉
https://hal.inria.fr/hal-01557599
Contributeur : Hal Ifip
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Soumis le : jeudi 6 juillet 2017 - 13:55:04
Dernière modification le : mercredi 27 décembre 2017 - 14:04:02
Document(s) archivé(s) le : mercredi 24 janvier 2018 - 23:27:07
Mandani Ntekouli, Maria Marouli, Georgia Konstantopoulou, George Anastassopoulos, Dimitrios Lymperopoulos. An Implementation of a Decision-Making Algorithm Based on a Novel Health Status Transition Model of Epilepsy. Lazaros Iliadis; Ilias Maglogiannis. 12th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), Sep 2016, Thessaloniki, Greece. IFIP Advances in Information and Communication Technology, AICT-475, pp.27-38, 2016, Artificial Intelligence Applications and Innovations. 〈10.1007/978-3-319-44944-9_3〉. 〈hal-01557599〉
