Medical diagnosis of Rheumatoid Arthritis using data-driven PSO–FCM with scarce datasets

Medical diagnosis of Rheumatoid Arthritis using data-driven PSO–FCM with scarce datasets


چاپ صفحه
پژوهان
صفحه نخست سامانه
چکیده مقاله
چکیده مقاله
نویسندگان
نویسندگان
دانلود مقاله
دانلود مقاله
دانشگاه علوم پزشکی تبریز
دانشگاه علوم پزشکی تبریز

نویسندگان: علیرضا صادقپور تیمور لوئی , امیر محمد نوالی

کلمات کلیدی: Diagnosis Rheumatoid Arthritis disease Decision Support System Fuzzy Cognitive Maps Particle Swarm Optimization Machine Learning

نشریه: 25103 , 2017 , 232 , 2017

اطلاعات کلی مقاله
hide/show

نویسنده ثبت کننده مقاله علیرضا صادقپور تیمور لوئی
مرحله جاری مقاله تایید نهایی
دانشکده/مرکز مربوطه دانشکده پزشکی
کد مقاله 64636
عنوان فارسی مقاله Medical diagnosis of Rheumatoid Arthritis using data-driven PSO–FCM with scarce datasets
عنوان لاتین مقاله Medical diagnosis of Rheumatoid Arthritis using data-driven PSO–FCM with scarce datasets
ناشر 4
آیا مقاله از طرح تحقیقاتی و یا منتورشیپ استخراج شده است؟ خیر
عنوان نشریه (خارج از لیست فوق)
نوع مقاله Original Article
نحوه ایندکس شدن مقاله ایندکس شده سطح یک – ISI - Web of Science
آدرس لینک مقاله/ همایش در شبکه اینترنت

خلاصه مقاله
hide/show

Rheumatoid Arthritis (RA) is a chronic autoimmune disease that affect joints and muscles, and can result in noticeable disruption of joint structure and function. Early diagnosis of RA is very crucial in preventing disease's progression. However, it is a complicated task for General Practitioners (GPs) due to the wide spectrum of symptoms, and progressive changes in disease's direction over time. In order to assist physicians, and to minimize possible errors due to fatigued or less-experienced physicians, this study proposes an advanced decision support tool based on consultations with a group of experienced medical professionals (i.e. orthopedic surgeons and rheumatologists), and using a well-known soft computing method called Fuzzy Cognitive Maps (FCMs). First, a set of criteria for diagnosis of RA, based on previous studies and consultation with medical professionals have been selected. Then, Particle Swarm Optimization (PSO) and FCMs along with medical experts' knowledge were used to model this problem and calculate the severity of the RA disease. Finally, a small-scale test has been conducted at Shohada University Hospital, Iran, for evaluating the accuracy of the proposed tool. Accuracy level of the tool reached to 90% and the results closely matched the medical professionals' opinions. Considering obtained results in real practice, we believe that the proposed decision support tool can assist GPs in an accurate and timely diagnosis of patients with RA. Ultimately, the risk of wrong or late diagnosis will be diminished, and patients’ disease may be prevented from moving through the advanced stages.

نویسندگان
hide/show

نویسنده نفر چندم مقاله
علیرضا صادقپور تیمور لوئیچهارم
امیر محمد نوالیسوم

لینک دانلود مقاله
hide/show

نام فایل تاریخ درج فایل اندازه فایل دانلود
Medical Diagnosis of Rheumatoid Arthritis using Data.pdf1397/08/15940621دانلود
Untitled.jpg1397/08/15121450دانلود