Please use this identifier to cite or link to this item: https://open.uns.ac.rs/handle/123456789/287
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dc.contributor.authorVidaković, Mirnaen
dc.contributor.authorĆosić, Đorđeen
dc.contributor.authorĆosić O.en
dc.contributor.authorKaštelan, Ivanen
dc.contributor.authorVelikić G.en
dc.date.accessioned2019-09-23T10:05:47Z-
dc.date.available2019-09-23T10:05:47Z-
dc.date.issued2019-05-20en
dc.identifier.isbn9781450361262en
dc.identifier.urihttps://open.uns.ac.rs/handle/123456789/287-
dc.description.abstract© 2019 Association for Computing Machinery. This paper describes one solution for embedding an Artificial Intelligence (AI) framework into the Decision Support System (DSS) used for a patient health assessment and life improvement. The DSS processes sensor-acquired health parameters and various health-related data in order to give an assessment of the patient health condition as well as to try to predict the possibility of the patient having another major health decline, such as stroke. The initial DSS version processes data using the statistical methods and proprietary algorithms which did not employ AI techniques. Rapid emergence of the AI frameworks, and evidence of clearly noticeable better results for systems based on AI, motivated us to integrate AI into the DSS. In this paper we present integration of TensorFlow framework in the DSS.en
dc.relation.ispartofACM International Conference Proceeding Seriesen
dc.titleAdding AI to the decision support system used in patient health assessmenten
dc.typeConference Paperen
dc.identifier.doi10.1145/3329189.3329246en
dc.identifier.scopus2-s2.0-85067838236en
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/85067838236en
dc.relation.lastpage402en
dc.relation.firstpage399en
item.fulltextNo Fulltext-
item.grantfulltextnone-
crisitem.author.deptDepartman za industrijsko inženjerstvo i menadžment-
crisitem.author.deptDepartman za računarstvo i automatiku-
crisitem.author.parentorgFakultet tehničkih nauka-
crisitem.author.parentorgFakultet tehničkih nauka-
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