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dc.contributor.authorPerera, B. D. K-
dc.contributor.authorWickramarathna, W.A.A.I.-
dc.contributor.authorChandrasiri, S-
dc.contributor.authorWanniarachchi, W.A.P.W-
dc.contributor.authorDilshani, S.H.N-
dc.contributor.authorPemadasa, N-
dc.date.accessioned2023-01-24T05:28:09Z-
dc.date.available2023-01-24T05:28:09Z-
dc.date.issued2022-10-15-
dc.identifier.citationB. D. K. Perera, W. A. A. I. Wickramarathna, S. Chandrasiri, W. A. P. W. Wanniarachchi, S. H. N. Dilshani and N. Pemadasa, "UveaTrack: Uveitis Eye Disease Prediction and Detection with Vision Function Calculation and Risk Analysis," 2022 IEEE 13th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON), Vancouver, BC, Canada, 2022, pp. 0088-0093, doi: 10.1109/IEMCON56893.2022.9946505.en_US
dc.identifier.isbn978-166546316-4-
dc.identifier.urihttps://rda.sliit.lk/handle/123456789/3157-
dc.description.abstractUveitis is an inflammatory infection that affects uvea tissue, the middle layer of the eyewall. It can result in swelling or damage to the eye and lead to vision impairments or blindness. Most Uveitis symptoms are associated with many other diseases localized to the eye. Thus, it is hard to determine the responsible symptoms for uveitis. Consequently, early detection of this disease can prevent a perilous situation in the future. The initial motivation behind the design of this mobile application is to help accurately diagnose uveitis with minimal time and effort and thereby minimize the shortage of human specialists in this field. The 'UveaTrack' is a hybrid mobile application that enables the keep tracking of uveitis eye illness and uses machine learning (ML) algorithms, deep learning (DL) architectures, and image processing techniques for developing the system. The 'UveaTrack' application could be able to achieve an average accuracy of more than 85% and had produced overall better results. Furthermore, the 'UveaTrack' application can use as a valuable instructional tool for freshly graduated clinicians, supporting their work with patients and assisting them in making diagnostics conclusions.en_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineersen_US
dc.relation.ispartofseries2022 IEEE 13th Annual Information Technology, Electronics and Mobile Communication Conference, IEMCON 2022;Pages 88 - 93-
dc.subjectDeep Learningen_US
dc.subjectDetectionen_US
dc.subjectImage Processingen_US
dc.subjectMachine Learningen_US
dc.subjectPredictionen_US
dc.subjectRisk Analysisen_US
dc.subjectUveitisen_US
dc.subjectVision Functionen_US
dc.titleUveaTrack: Uveitis Eye Disease Prediction and Detection with Vision Function Calculation and Risk Analysis Publisher: IEEE Cite This PDFen_US
dc.typeArticleen_US
dc.identifier.doi10.1109/IEMCON56893.2022.9946505en_US
Appears in Collections:Department of Information Technology

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