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dc.contributor.authorMuzamil, Sohail
dc.contributor.authorHussain, Tassadaq
dc.contributor.authorHaider, Amna
dc.contributor.authorWaraich, Umber
dc.contributor.authorAshiq, Umair
dc.contributor.authorAyguadé Parra, Eduard
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors
dc.contributor.otherBarcelona Supercomputing Center
dc.identifier.citationMuzamil, S. [et al.]. An intelligent iris based chronic kidney identification system. "Symmetry", 12 Desembre 2020, vol. 12, núm. 12, article 2066, p. 1-14.
dc.description.abstractIn recent years, the demand for alternative medical diagnostics of the human kidney or renal is growing, and some of the reasons behind this relate to its non-invasive, early, real-time, and pain-free mechanism. The chronic kidney problem is one of the major kidney problems, which require an early-stage diagnosis. Therefore, in this work, we have proposed and developed an Intelligent Iris-based Chronic Kidney Identification System (ICKIS). The ICKIS takes an image of human iris as input and on the basis of iridology a deep neural network model on a GPU-based supercomputing machine is applied. The deep neural network models are trained while using 2000 subjects that have healthy and chronic kidney problems. While testing the proposed ICKIS on 2000 separate subjects (1000 healthy and 1000 chronic kidney problems), the system achieves iris-based chronic kidney assessment with an accuracy of 96.8%. In the future, we will work to improve our AI algorithm and try data-set cleaning, so that accuracy can be increased by more efficiently learning the features.
dc.description.sponsorshipThis work is supported by the Higher Education Commission (HEC) of Pakistan under the Technology Development Fund with project Number TDF03-097 and National Research Program for Universities (NRPU) with project grant no. 8153/Federal/NRPU/R&D/HEC/2017.
dc.format.extent14 p.
dc.rightsAttribution 4.0 International
dc.subjectÀrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica::Bioinformàtica
dc.subjectÀrees temàtiques de la UPC::Informàtica::Intel·ligència artificial
dc.subject.lcshArtificial intelligence -- Medical applications
dc.subject.lcshKidneys -- Diseases -- Diagnosis
dc.subject.otherEmbedded computer vision
dc.titleAn intelligent iris based chronic kidney identification system
dc.subject.lemacIntel·ligència artificial -- Aplicacions a la medicina
dc.subject.lemacRonyons -- Malalties -- Diagnòstic
dc.contributor.groupUniversitat Politècnica de Catalunya. CAP - Grup de Computació d'Altes Prestacions
dc.description.peerreviewedPeer Reviewed
dc.rights.accessOpen Access
dc.description.versionPostprint (published version)
local.citation.authorMuzamil, S.; Hussain, T.; Haider, A.; Waraich, U.; Ashiq, U.; Ayguadé, E.
local.citation.number12, article 2066

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