J. Sarivougioukas, Aristides Th. Vagelatos
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引用次数: 21
Modeling Deep Learning Neural Networks With Denotational Mathematics in UbiHealth Environment
Ubiquitous computing environments that are involved in healthcare applications are typically characterized bydynamically changing contexts.The contextual information must be efficiently processed in order to support medical decision making. The ubiquitous computing healthcare ecosystemmustbecapableofextractingmedicallyvaluablecharacteristics,makingprecisedecisions, andtakingmedicallyappropriateactions.Inthisframework,deeplearningnetworkscanbeused fordatafusionoflargeandcomplexsetsofinformationinordertomaketheappropriatemedical diagnoses.Thequalityofdecisionsdependsontheselectionofappropriatenetworkweights,which definea transformationof thegiven input intoadiagnosis.Denotationalmathematicsprovidea promisingframeworkformodelingdeeplearningnetworksandadjustingtheirbehaviorbyadapting theirweightsforthegiveninput.Furthermore,thefidelityofthenetwork’soutputcanbecontrolled byapplyingaregulatortotheweightsvalues.TheauthorsshowthatDenotationalMathematicscan serveasarigorousframeworkformodelingandcontrollingdeeplearningnetworks,therebyenhancing thequalityofmedicaldecisionmaking. KEyWoRDS Deep Learning Neural Networks, Denotational Mathematics, UbiComp, UbiHealth
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