Information System of Personalized Patient's Adherence Level Determination; Studies in Health Technology and Informatics; Vol. 237 : Wearable, Micro and Nano Technologies for Personalised Health (pHealth 2017)

Λεπτομέρειες βιβλιογραφικής εγγραφής
Parent link:Studies in Health Technology and Informatics
Vol. 237 : Wearable, Micro and Nano Technologies for Personalised Health (pHealth 2017).— 2017.— [P. 68 - 72]
Κύριος συγγραφέας: Taranik M. A. Maksim Alekseevich
Συγγραφή απο Οργανισμό/Αρχή: Национальный исследовательский Томский политехнический университет (ТПУ) Институт кибернетики (ИК) Кафедра программной инженерии (ПИ)
Άλλοι συγγραφείς: Kopanitsa G. D. Georgy Dmitrievich
Περίληψη:Title screen
The present paper deals with intellectual system for determination and evaluation of personalized patient's level of adherence. The most popular nowadays techniques for adherence evaluation are interview and questionnaires. We propose a new automated approach based on the comparison of direct patient's data with personalized treatment plan using fuzzy logic and standard ISO 13606. On the current step, we process only manually submitted data. For the next step we are going to introduce sensor devices for the purposes of personalized patients' adherence determination. The results can be useful for medical organizations with long-term patients.
Режим доступа: по договору с организацией-держателем ресурса
Γλώσσα:Αγγλικά
Έκδοση: 2017
Θέματα:
Διαθέσιμο Online:http://ebooks.iospress.nl/publication/46423
Μορφή: xMaterials Ηλεκτρονική πηγή Κεφάλαιο βιβλίου
KOHA link:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=655163

MARC

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330 |a The present paper deals with intellectual system for determination and evaluation of personalized patient's level of adherence. The most popular nowadays techniques for adherence evaluation are interview and questionnaires. We propose a new automated approach based on the comparison of direct patient's data with personalized treatment plan using fuzzy logic and standard ISO 13606. On the current step, we process only manually submitted data. For the next step we are going to introduce sensor devices for the purposes of personalized patients' adherence determination. The results can be useful for medical organizations with long-term patients. 
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