An Approach for Detecting Missed Tissue Proteins in Autoimmune Diseases
dc.contributor.author | ElKafrawy, Passent | |
dc.contributor.author | Rafea, Mahmoud | |
dc.contributor.author | Elnemr, Rasha | |
dc.date.accessioned | 2023-04-19T07:33:39Z | |
dc.date.available | 2023-04-19T07:33:39Z | |
dc.date.issued | 2023-01 | |
dc.identifier.uri | http://hdl.handle.net/20.500.14131/711 | |
dc.description.abstract | Autoimmune 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.publisher | IEEE | en_US |
dc.subject | disease diagnosis, autoimmune diseases, missed tissue protein, Erythrocytes Dynamic Antigens Store (EDAS) | en_US |
dc.title | An Approach for Detecting Missed Tissue Proteins in Autoimmune Diseases | en_US |
dc.contributor.researcher | External Collaboration | en_US |
dc.contributor.lab | Artificial Intelligence & Cyber Security Lab | en_US |
dc.subject.KSA | ICT | en_US |
dc.source.index | Scopus | en_US |
dc.contributor.department | Computer Science | en_US |
dc.contributor.firstauthor | Elnemr, Rasha | |
dc.conference.location | Effat University | en_US |
dc.conference.name | The 20th International Learning and Technology Conference | en_US |
dc.conference.date | 2023-01-26 |