A web-based fuzzy risk predictive-decision model of de novo stress urinary incontinence in women undergoing pelvic organ prolapse surgery

A web-based fuzzy risk predictive-decision model of de novo stress urinary incontinence in women undergoing pelvic organ prolapse surgery


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دانشگاه علوم پزشکی تبریز
دانشگاه علوم پزشکی تبریز

نویسندگان: یلدا موسوی , طاها صمدسلطانی , سکینه حاج ابراهیمی

کلمات کلیدی: Expert system; Fuzzy logic; Pelvic organ prolapse surgery; Risk prediction; Stress urinary incontinence

نشریه: 8871 , 1 , 15 , 2021

اطلاعات کلی مقاله
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نویسنده ثبت کننده مقاله طاها صمدسلطانی
مرحله جاری مقاله تایید نهایی
دانشکده/مرکز مربوطه دانشکده مدیریت و اطلاع رسانی پزشکی
کد مقاله 76558
عنوان فارسی مقاله A web-based fuzzy risk predictive-decision model of de novo stress urinary incontinence in women undergoing pelvic organ prolapse surgery
عنوان لاتین مقاله A web-based fuzzy risk predictive-decision model of de novo stress urinary incontinence in women undergoing pelvic organ prolapse surgery
ناشر 3
آیا مقاله از طرح تحقیقاتی و یا منتورشیپ استخراج شده است؟ بلی
عنوان نشریه (خارج از لیست فوق)
نوع مقاله Original Article
نحوه ایندکس شدن مقاله ایندکس شده سطح دو – PubMed
آدرس لینک مقاله/ همایش در شبکه اینترنت

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Background: Pelvic organ prolapse (POP) and stress urinary incontinence (SUI) are common conditions affecting women's health and quality of life. In 50% of cases, SUI occurs after POP surgery, which is called de novo SUI. Predicting the risk of de novo SUI is a complex multi-attribute decision-making process. The current study made available a Decision Support System in the form of a fuzzy calculator web-based application to help surgeons predict the risk of de novo SUI. Materials and methods: We first identified 12 risk factors and the diagnostic criteria for de novo SUI by means of a systematic review of the literature. Then based upon an expert panel, all risk factors were prioritized. A set of 232 fuzzy rules for the prediction of de novo SUI was determined. A fuzzy expert system was developed using MATLAB software and Mamdani Inference System. The risk prediction model was then evaluated using retrospective data extracted from 30 randomly selected medical records of female patients over the age of 50 without symptoms of urinary incontinence who had undergone POP surgery. Finally, the proposed results of the predictive system were compared with the results of retrospective medical record data review. Results: The results of this online calculator show that the accuracy of this risk prediction model, at more than 90%, compared favorably to other SUI risk prediction models. Conclusions: A fuzzy logic-based clinical Decision Support System in the form of an online calculator for calculating SUI prognosis after POP surgery in women can be helpful in predicting de novo SUI.

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نویسنده نفر چندم مقاله
یلدا موسویاول
طاها صمدسلطانیدوم
سکینه حاج ابراهیمیسوم

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1.pdf1400/07/101616723دانلود