چکیده

Systemic Lupus Erythematosus (SLE) is an autoimmune disease in which the immune system attacks its own tissues, causing widespread inflammation and tissue damage in the affected organs. It can affect the joints, skin, brain, lungs, kidneys, and blood vessels. Despite its potentially significant impact on disease outcome, nervous system involvement in systemic lupus erythematosus has received little attention. It is likely that the immune system dysfunction arises from years before the onset of the clinical disease, which makes it a particularly challenging disease. Our aim is to identify the lupus patients likely to have seriously damaged brain by exploring their cases. We can identify and then develop a classification for the prediction of brain infection in patients with SLE to prevent brain infection. Firstly, as too many features were extracted, using logistic regression, we select five most important ones. Next, the suggested neural network makes us a classification. This modeling, which has been done using Python, gives us more insight than the classification model of the logistic regression model.

کليدواژه ها

Logistic regression, Neural network, Classification, Systemic lupus erythematosus, Brain inflammation, Neuropsychiatric Lupus

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منصوره صبور گیاهی , 1400 , پیش بینی لوپوس عصبی- روانی در بیماران لوپوس اریتماتوز سیستمیک با تجزیه و تحلیل سوابق بالینی با استفاده از شبکه عصبی , نخستین همایش بین المللی و سومین همایش ملی ریاضیات زیستی