-ارایه یک مدل هوشمند فازی در مدیریت عدم قطعیت در تشخیص مرحله پیشرفت سرطان سینه

نوع مقاله : مقاله پژوهشی

نویسندگان

1 کارشناسی ارشد هوش مصنوعی، گروه مهندسی کامپیوتر، واحد شهر قدس، دانشگاه آزاد اسلامی، تهران، ایران. رایانامه: leilahonari@gmail.com

2 استادیار، گروه مهندسی کامپیوتر، واحد شهر قدس، دانشگاه آزاد اسلامی، تهران، ایران. رایانامه: rahil.hosseini@qodsiau.ac.ir

3 استادیار، گروه مهندسی برق-الکترونیک، واحد شهر قدس، دانشگاه آزاد اسلامی، تهران، ایران. رایانامه: Mahdi.mazinani@qodsiau.ac.ir

چکیده

در سال های اخیر سسیتم های هوشمند تصمیم یار موردتوجه پژوهش های فراوانی جهت مدیریت عدم قطعیت در تشخیص های پزشکی قرار گرفته است. باتوجه به ابهام در تشخیص مراحل سرطان پستان که یکی از دلایل عمده و اصلی مرگ ومیر زنان در دهه اخیر بوده است، تشخیص زودهنگام مرحله پیشرفت سرطان می تواند شانس بهبودی کامل را افزایش دهد تا بهترین گزینه درمان انتخاب شود. در این پژوهش مدلی جهت مدیریت عدم قطعیت مبتنی بر منطق فازی با امکان مدیریت عدم قطعیت در ورودی‌ها و خروجی‌ها در مرحله بندی سرطان سینه، ارائه می‌شود. در این مطالعه، پرونده پزشکی400بیمار مبتلابه سرطان پستان با تعداد 3 ویژگی مورد بررسی قرارگرفته ونتایج آن توسط گروهی از متخصصان خبره موردبررسی قرارگرفته است. نتایج به‌دست‌آمده کارایی سیستم با استفاده از روش تحلیل منحنی ROC مورد بررسی قرار گرفت که میزان صحت عملکرد به ترتیب برای مراحل 1و4 سرطان سینه97/50 درصد،و98/46 درصد از جنبه معیار سطح زیر منحنی بدست آمده است.

کلیدواژه‌ها

عنوان مقاله [English]

An Intelligent Fuzzy Model for Managing Uncertainty in Diagnosis of the Breast Cancer Staging

نویسندگان [English]

  • Leila Honari mahmod 1
  • Rahil Hosseini 2
  • Mahd Mazinani 3
1 MSc. Faculty of Engineering, Department of Computer Engineering, Islamic Azad University, Tehran, Iran. Email: rahil.hosseini@qodsiau.ac.ir
2 Assistant Prof., Faculty of Engineering, Department of Computer Engineering, Islamic Azad University, Tehran, Iran. Email: leilahonari@gmail.com
3 Assistant Prof., Faculty of Engineering, Department of Electrical Engineering, Islamic Azad University, Tehran, Iran. Email: Mahdi.mazinani@qodsiau.ac.ir
چکیده [English]

Intelligent assistant systems have been focused in many researches for managing uncertainties in medical diagnosis in the recent years. Due to vagueness in diagnosis of Breast cancer stages which is one of the major cause of death in women, early diagnosis of stages of this cancer can help physicians to choose the best treatment option. In this research, an intelligent
Model based on fuzzy logic has been presented to manage uncertainty associated with input and outputs in the diagnosis of stages of breast cancer. This model implements human experience with membership functions and fuzzy rules and is a general method for combining knowledge, intelligent technology, control and decision making. In this study, the medical records of 400 patients with breast cancer with 3 features were studied and their results were evaluated by a group of experts. The results of the system efficiency were investigated using an ROC curve analysis method. The specificity, sensitivity and accuracy in steps 1, 4 of the Breast cancer were (97/50%, 98/43% ), in order.

کلیدواژه‌ها [English]

  • Breast cancer
  • fuzzy logic
  • Mamdani fuzzy inference system
  • Modelling uncertainty

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