A respiration-status diagnostic certainty-factors system based on blood gases measurements

Tzafestas, SG; Tzafestas, ES; Marinos, A; Behrakis, P

dc.contributor.author	Tzafestas, SG	en
dc.contributor.author	Tzafestas, ES	en
dc.contributor.author	Marinos, A	en
dc.contributor.author	Behrakis, P	en
dc.date.accessioned	2014-03-01T01:45:52Z
dc.date.available	2014-03-01T01:45:52Z
dc.date.issued	1997	en
dc.identifier.issn	01371223	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/24763
dc.relation.uri	http://www.scopus.com/inward/record.url?eid=2-s2.0-0031340911&partnerID=40&md5=b798c2a8d72e1d2368a2a084de79b85c	en
dc.subject.other	Artificial intelligence	en
dc.subject.other	Blood gas analysis	en
dc.subject.other	Expert systems	en
dc.subject.other	Patient monitoring	en
dc.subject.other	Real time systems	en
dc.subject.other	Respiratory therapy	en
dc.subject.other	Diagnostic expert systems	en
dc.subject.other	Respiration status diagnosis systems	en
dc.subject.other	Computer aided diagnosis	en
dc.title	A respiration-status diagnostic certainty-factors system based on blood gases measurements	en
heal.type	journalArticle	en
heal.publicationDate	1997	en
heal.abstract	This paper presents a respiration status diagnosis system (called RDPB2) which is based on the measurement of the blood gases. This system embodies and uses extensive available medical knowledge, concerning the relation of the patient's respiration state with the type and concentrations of the gases that exist in his/her blood. RDPB2 employs both simple (standard) medical diagnosis techniques and newer sophisticated techniques, which can detect permanent situations of the patient. These latter techniques take into account the distance of the patient state from the straight lines that define the various regions of the pH/paCO2 diagram, as well as the ""medical weighting"" of these regions. The system can compare each new measurement with the previous one, and so provides a good picture of the relative state of the patient with reference to the elapsed time interval. To deal with the ambiguity/uncertainty induced when the measurements suggest that the patient belongs to the border of regions or to overlapping regions, the certainty factors reasoning model of the MYCIN expert system is employed. This way a highly reliable diagnosis is achieved in all cases. The system can operate in ""real-time"" under any conditions, and so is suitable for continuous monitoring of the patient in a hospital environment.	en
heal.journalName	Systems Science	en
dc.identifier.volume	23	en
dc.identifier.issue	2	en
dc.identifier.spage	45	en
dc.identifier.epage	61	en