-طبقه بندی شدت اختلال ‌اُتیسم بااستفاده از روش‌های فازی مبتنی بر محاسبات نرم

نوع مقاله : مقاله پژوهشی

نویسندگان

1 کارشناسی ارشد مهندسی کامپیوتر، دانشکده فنی‌‌ مهندسی، واحد شهر قدس، دانشگاه آزاد اسلامی، تهران، ایران. رایانامه: saberipour.n@gmail.com

2 استادیار، دانشکده فنی‌‌مهندسی، واحد شهر قدس، دانشگاه آزاد اسلامی، تهران، ایران. رایانامه: mahdi.mazinani@qodsiau.ac.ir

3 استادیار، دانشکده فنی‌‌مهندسی، واحد شهر قدس، دانشگاه آزاد اسلامی، تهران، ایران. رایانامه‌: rahil.hosseini@gmail.com

چکیده

جمعیت قابل‌ملاحظه‌ای از افراد، در هر جامعه‌ای مبتلا به اختلال اُتیسم هستند. یکی از معضلات در زمینه تشخیص اختلال ‌اُتیسم وجود عدم قطعیت در تعیین سطح شدت این بیماری است. بدین منظور در این پژوهش برای بر طرف نمودن این مشکل روش‌های مبتنی بر سیستم‌های فازی ارائه گردیده است. روش‌های ارائه‌شده بر روی 112 داده‌ مربوط به کودک و نوجوان بین گروه سنی ۳ تا ۱۴ سال است. که از مراکز مختلف توان‌بخشی واقع در تهران جمع‌آوری و اعمال گردیده است. میانگین صحت عملکرد روش‌های مطرح‌شده بااستفاده از روش الگوریتم ژنتیک با میزان سطح زیر منحنی ROC 4/97 درصد از قابلیت اطمینان و کارایی بهتری در مقایسه با سایر روش‌های پیشنهادی (الگوریتم سیستم استنتاج عصبی فازی تطبیقی) در این پژوهش برخوردار است. سیستم طراحی‌شده در این مقاله می‌تواند به‌عنوان یک روش کمک تشخیص پزشکی برای پزشکان مورداستفاده قرار گیرد.

کلیدواژه‌ها

عنوان مقاله [English]

Classification of Autism Disorder Severity Using Fuzzy Methods Based on Soft Computing

نویسندگان [English]

  • Nahid Saberipour 1
  • Mahdi Mazinani 2
  • Rahil Hosseini 3
1 Master of Computer Engineering, Faculty of Engineering, Ghods Branch, Islamic Azad University, Tehran, Iran. Email: saberipour.n@gmail.com
2 Assistant Professor, Faculty of Engineering, Ghods Branch, Islamic Azad University, Tehran, Iran. Email: mahdi.mazinani@qodsiau.ac.ir
3 Assistant Professor, Faculty of Engineering, Ghods Branch, Islamic Azad University, Tehran, Iran. Email: rahil.hosseini@gmail.com
چکیده [English]

A significant proportion of population in each community suffer from autism disorder. One of the challenges in diagnosing autism is the uncertainty in determining the severity of the disease. To this end, fuzzy systems based methods have been adopted in this study. The presented methods are based on 112 data driven from children and adolescents between the ages of 3 to 14 years. These data were collected from various rehabilitation centers in Tehran. The average performance accuracy of the proposed methods Using Genetic Algorithm with area under curve ROC compared to other methods (adaptive fuzzy neural inference system algorithm) proved to be 97/4% more reliable and efficient. The system designed in this article can be used as a medical diagnostics help tool for physicians.

کلیدواژه‌ها [English]

  • Autism Disorder
  • Adaptive Neural-Fuzzy Inference System
  • GARS test
  • Genetic Algorithm
  • Fuzzy System

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