A framework for personalized decision support system for the healthcare application

dc.contributor.author	Muthuraman, Thangaraj	en
dc.contributor.author	Sankaran, Gnanambal	en
dc.date.accessioned	2014-07-20T21:44:56Z
dc.date.available	2014-07-20T21:44:56Z
dc.date.issued	2014-07-21
dc.identifier.uri	http://hdl.handle.net/11400/1500
dc.rights	Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ηνωμένες Πολιτείες	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/us/	*
dc.source	www.hsj.gr	en
dc.subject	decision support systems
dc.subject	endemic goiter
dc.subject	Ontology
dc.subject	Recommender systems (Information filtering)
dc.subject	Οντολογία
dc.subject	Παραμετροποιημένη νοσοκομειακή φροντίδα
dc.subject	Iodine diet ontology
dc.subject	Personalized healthcare
dc.subject	Semantic Web Rule Language (SWRL)
dc.title	A framework for personalized decision support system for the healthcare application	en
heal.type	journalArticle
heal.generalDescription	Research article	en
heal.classification	Medicine
heal.classification	Information Technology and Systems Architecture
heal.classification	Ιατρική
heal.classification	Τεχνολογία
heal.classificationURI	http://id.loc.gov/authorities/subjects/sh00006614
heal.classificationURI	http://zbw.eu/stw/thsys/73341
heal.classificationURI	N/A-Ιατρική
heal.classificationURI	N/A-Τεχνολογία
heal.keywordURI	http://lod.nal.usda.gov/31914
heal.keywordURI	http://lod.nal.usda.gov/148902
heal.keywordURI	http://id.loc.gov/authorities/subjects/sh85094833
heal.keywordURI	http://id.loc.gov/authorities/subjects/sh2007003098
heal.language	en
heal.access	free
heal.recordProvider	Τεχνολογικό Εκπαιδευτικό Ίδρυμα Αθήνας.Σχολή Επαγγελμάτων Υγείας και Πρόνοιας. Τμήμα Νοσηλευτικής	el
heal.publicationDate	2014-04
heal.bibliographicCitation	Muthuraman, T. & Sankaran, G. (April 2014). A framework for personalized decision support system for the healthcare application. “Health Science Journal”. 8(2):262-273.	en
heal.abstract	Background: The main objective of healthcare system is at once to enhance the quality of treatment and to have a check on the consumption of time and cost. Improving the quality of the health care system is to adapt to a semantic system, which is more easily understood by man and machine than the syntactic based system. Objective: In this research work, a framework for personalized decision support system is analyzed. To illustrate the framework, the well known medical decision-making problem of the thyroid gland and obesity is used. Methods: The developed framework constructs a fuzzy decision tree and the fuzzy rules are created from fuzzy decision tree. Then a medical expert evaluates the rules involved in the decision making process. Based on the decision, the system triggers the Semantic Web Rule Language (SWRL) that produces a treatment procedure. Results: The results of the framework provide the user-friendly environment for nurses, physicians and patients. The derived facts are automatically updated into ontology. Therefore it creates a dynamic process. The main goal of the developed framework is to provide personalized treatment flow without the intervention of domain experts. The implemented architecture provides good performance with respect to memory. The proposed automatic food recommendation system acts as a helping hand for people by saving many medical formalities and also reducing the time of domain experts. Conclusion: The proposed framework has the ability to automatically trigger the rules and make the treatment recommendations. Therefore it reduces the required time of care providers, patients and saves many medical resources.	en
heal.publisher	Μαρβάκη, Χριστίνα	el
heal.journalName	Health Science Journal	en
heal.journalType	peer-reviewed
heal.fullTextAvailability	true