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dc.contributor.authorRattadilok, P.
dc.contributor.authorMahfouf, M.
dc.contributor.authorRoss, J.J.
dc.contributor.authorMills, G.H.
dc.contributor.authorPanoutsos, G.
dc.contributor.authorZeghbib, A.
dc.contributor.authorDenai, Mouloud
dc.identifier.citationRattadilok , P , Mahfouf , M , Ross , J J , Mills , G H , Panoutsos , G , Zeghbib , A & Denai , M 2012 , ' Suggestive Therapeutic Pathways Using Hyper-Heuristics ' Paper presented at 8th IFAC Symposium on Biological and Medical Systems , Budapest , Hungary , 29/08/12 - 31/08/12 , pp. 397-402 .
dc.identifier.otherPURE: 2915788
dc.identifier.otherPURE UUID: b9f64eb3-2f37-401c-89e6-52e19ff9b363
dc.identifier.otherScopus: 84881052628
dc.description.abstractTherapeutic decision support can be used to promptly assist clinical decision making process. This paper presents a novel approach to interpreting multiple data streams in intensive care environments, the resulting model can be used to correct and maintain patients' health whilst treating underlying illnesses. Rather than simply directing which treatments to be applied, multiple suggestive treatment pathways can be provided allowing several "what-if" scenarios to choose from. Hyper-heuristics are used to guide the treatments and therapeutic pathways selection. Algorithmic validation is made using a human cardiovascular system model parameterised with various post surgery conditionsen
dc.titleSuggestive Therapeutic Pathways Using Hyper-Heuristicsen
dc.contributor.institutionSchool of Engineering and Technology
dc.contributor.institutionScience & Technology Research Institute
dc.contributor.institutionCentre for Engineering Research
dc.contributor.institutionSmart Electronics Devices and Networks
dc.description.statusNon peer reviewed

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