Web-based CBR System for Support Medical Diagnosis

dc.contributor.author	Stamenov, Alexander
dc.contributor.author	Koychev, Ivan
dc.date.accessioned	2009-11-24T15:45:05Z
dc.date.available	2009-11-24T15:45:05Z
dc.date.issued	2009-10-29
dc.identifier.citation	Stamenov, Al., Koychev, I. Web-based CBR System for Support Medical Diagnosis, Proceedings of International Conference on SOFTWARE, SERVICES & SEMANTIC TECHNOLOGIES, October 28-29, 2009, Sofia, Bulgaria, ISBN 978-954-9526-62-2	bg_BG
dc.identifier.isbn	978-954-9526-62-2
dc.identifier.uri	http://hdl.handle.net/10506/240
dc.description.abstract	From the early days of development of Artificial Intelligence, there was a strong in-terest in applications in the area of medicine. The interest was strong enough to form a separate branch in the early ‘80s entitled Artificial Intelligence in Medicine (AIM). DXplain [1] is an illustration of system from this early period. It is an internal medi-cine expert system developed at the Massachusetts General Hospital that is still in use at a number of hospitals and medical schools, mostly for clinical education purposes. Rather than using an expert system approach or another rule-inferring paradigm we decided to employ a Case-based Reasoning (CBR) methodology [4]. Storing and searching among past cases has an advantage in complex domains where it is difficult to create a global theory that explains most of the existing cases.	bg_BG
dc.language.iso	en	bg_BG
dc.publisher	Demetra EOOD	bg_BG
dc.subject	Web-based CBR System	bg_BG
dc.subject	Medical Diagnosis	bg_BG
dc.title	Web-based CBR System for Support Medical Diagnosis	bg_BG
dc.type	Article	bg_BG