ارائه روشی برای تشخیص بیماری کووید-19 بر پایه الگوریتم روابط اجتماعی درختان و طبقه‌بند نایو بیز

نوع مقاله : مقاله پژوهشی

نویسندگان

گروه مهندسی کامپیوتر، واحد رشت، دانشگاه آزاد اسلامی، رشت، ایران.

چکیده

بیماری کووید-۱۹ که به طور عمده به عنوان کرونا شناخته می‌شود، یک بیماری ویروسی است که توسط ویروس SARS-CoV-2 ایجاد می‌گردد. علائم رایج این بیماری شامل تب، سرفه، احساس خستگی و از دست دادن حس بویایی می‌باشد. روش استاندارد برای تشخیص دقیق کووید-۱۹، آزمایش rRT-PCR که نیازمند نمونه‌برداری تنفسی است که زمانبر می‌باشد. بنابراین توسعه روش‌های تشخیصی سریع این بیماری اهمیت زیادی دارد.در این مقاله‌ روشی جدید برای تشخیص کووید-۱۹ با استفاده از هوش مصنوعی معرفی شده است. این روش، که سریع و غیرتهاجمی است، بر اساس الگوریتم روابط اجتماعی درختان (TSR) و طبقه‌بندی نایو بیز طراحی شده است. روش پیشنهادی شامل دو مرحله اصلی انتخاب ویژگی و تشخیص بیماری است. انتخاب ویژگی‌ها با استفاده از الگوریتم TSR و تشخیص بیماری توسط طبقه‌بند نایو بیز انجام می‌شود. روش پیشنهاد شده به صورت عملی با مجموعه داده COVID-19 Dataset بررسی شد. ارزیابی‌های عملی نشان داده‌اند که این روش جدید در تشخیص کووید-۱۹ عملکرد بهتری نسبت به سایر روش‌های موجود دارد و تشخیص این بیماری را به صورت متوسط با دقت 96 درصد، فراخوانی 97 درصد و امتیاز-F1 96 درصد انجام می‌دهد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

A method for diagnosing the disease of Covid-19 based on the trees social relations optimization algorithm and Naive bayes classifier

نویسندگان [English]

  • Hossein Azgomi
  • Azam Andalib
Department of computer engineering, Rasht Branch, Islamic Azad University, Rasht, Iran.
چکیده [English]

COVID-19, mainly known as Corona, is a viral disease caused by the SARS-CoV-2 virus. The symptoms of COVID-19 include fever, fatigue, cough, and a loss of the sense of smell. The rRT-PCR test, as the standard diagnostic tool for this disease, requires respiratory sampling, which is time-consuming. Therefore, developing rapid diagnostic methods is of great importance. In this paper, a novel, rapid, and non-invasive method for diagnosing COVID-19 using artificial intelligence is introduced. This method comprises two stages: feature selection and disease diagnosis, which are performed using the Tree Social Relationships (TSR) algorithm and the Naive Bayes classifier. The proposed method is practically evaluated using the COVID-19 Dataset. Experimental evaluations show that this method outperforms existing approaches in diagnosing COVID-19, achieving 96% accuracy, 97% recall, and a 96% F1-score.

کلیدواژه‌ها [English]

  • Covid-19
  • Data mining
  • Tree social relationships algorithm
  • Naive bayes
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