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dc.contributor.authorElKafrawy, Passent
dc.contributor.authorRafea, Mahmoud
dc.contributor.authorElnemr, Rasha
dc.date.accessioned2023-04-19T07:33:39Z
dc.date.available2023-04-19T07:33:39Z
dc.date.issued2023-01
dc.identifier.urihttp://hdl.handle.net/20.500.14131/711
dc.description.abstractAutoimmune disease is a pathologic condition resulting from an induced error in the immune system leading to an autoimmune response with organ dysfunction or tissue damage. The discovery of autoantibodies in the blood is essential in the diagnosis of these diseases. Notice that the antibodies may not be the essential reason for the disease. It should be remarked that auto-antibodies are commonly found in all immunologically competent people and can increase during disease, infection, or injury. In some cases, autoantibodies can be the result, not the reason, of the disorder process. The existence of autoantibody responses has major significance in the diagnosis and prognosis of several autoimmune disorders. The goal of this work is to detect the set of missed tissue proteins that can be used in the diagnosis and treatment of a specific autoimmune disease. A hypothetical EDAS is generated. Ten thousand records are randomly created based on the mathematical model. The developed algorithm for missed tissue protein discovery is described. The presented tool can be used to diagnose autoimmune diseases in clinical laboratories.en_US
dc.publisherIEEEen_US
dc.subjectdisease diagnosis, autoimmune diseases, missed tissue protein, Erythrocytes Dynamic Antigens Store (EDAS)en_US
dc.titleAn Approach for Detecting Missed Tissue Proteins in Autoimmune Diseasesen_US
dc.contributor.researcherExternal Collaborationen_US
dc.contributor.labArtificial Intelligence & Cyber Security Laben_US
dc.subject.KSAICTen_US
dc.source.indexScopusen_US
dc.contributor.departmentComputer Scienceen_US
dc.contributor.firstauthorElnemr, Rasha
dc.conference.locationEffat Universityen_US
dc.conference.nameThe 20th International Learning and Technology Conferenceen_US
dc.conference.date2023-01-26


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