e-Doctor:

dc.contributor.author	Καμπουράκη, Α,	el
dc.contributor.author	Βάσσης, Δημήτριος	el
dc.contributor.author	Μπέλσης, Πέτρος	el
dc.contributor.author	Σκουρλάς, Χρήστος Π.	el
dc.date.accessioned	2015-05-21T19:54:26Z
dc.date.available	2015-05-21T19:54:26Z
dc.date.issued	2015-05-21
dc.identifier.uri	http://hdl.handle.net/11400/10858
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	http://www.sciencedirect.com/science/article/pii/S1877042813003716#	el
dc.subject	Automatic diagnosis
dc.subject	Αυτόματη διάγνωση
dc.subject	Medical
dc.subject	Ιατρική
dc.subject	SVM
dc.title	e-Doctor:	en
heal.type	journalArticle
heal.secondaryTitle	a web based support vector machine for automatic medical diagnosis	en
heal.generalDescription	Δημοσιευμένο και στο: 2nd International Conference on Integrated Information (IC-ININFO 2012)	el
heal.classification	Technology
heal.classification	Computer science
heal.classification	Τεχνολογία
heal.classification	Πληροφορική
heal.classificationURI	http://zbw.eu/stw/descriptor/10470-6
heal.classificationURI	http://skos.um.es/unescothes/C00750
heal.classificationURI	N/A-Τεχνολογία
heal.classificationURI	N/A-Πληροφορική
heal.identifier.secondary	doi:10.1016/j.sbspro.2013.02.078
heal.language	en
heal.access	campus
heal.recordProvider	Τεχνολογικό Εκπαιδευτικό Ίδρυμα Αθήνας. Σχολή Τεχνολογικών Εφαρμογών. Tμήμα Μηχανικών Πληροφορικής Τ.Ε	el
heal.publicationDate	2013-02-27
heal.bibliographicCitation	Kampouraki, A., Vassis, D., Belsis, P. and Skourlas, C. (2013). e-Doctor: a web based support vector machine for automatic medical diagnosis. In Proceedings of the 2nd International Conference on Integrated Information (IC-ININFO 2012), Budapest, Hungary, August 30 – September 3, 2012. "Procedia - Social and Behavioral Sciences", vol. 73, 27 February 2013. pp. 467–474. Available from: http://www.sciencedirect.com/science/article/pii/S1877042813003716#. [Accessed 09/04/2013]	en
heal.abstract	This paper proposes e-doctor; a web-based application that makes automatic diagnoses about health problems. The whole procedure is based on Support Vector Machines (SVMs), which are supervised learning models that analyze data and proceed to decisions, based on their knowledge. System administrators define specific characteristics for each health problem that can be diagnosed, and educate the SVM by entering sample files of statistical data. After that, medical staff can enter exam information about patients, and e-doctor makes an automatic diagnosis/prediction by means of answering if the patient has (or may have in the future) a specific health problem. The application can be used in cases where statistical information plays a vital role on deciding about a patient's condition. A prototype was developed and the system trained and tested for the case of heart symptoms. The results were satisfactory.	en
heal.journalName	Procedia - Social and Behavioral Sciences	en
heal.journalType	peer-reviewed
heal.fullTextAvailability	true