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

ازگومی, حسین; عندلیب, اعظم

doi:10.22052/scj.2025.254698.1239

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

نوع مقاله : مقاله پژوهشی

نویسندگان

حسین ازگومی

اعظم عندلیب

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

10.22052/scj.2025.254698.1239

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

کووید-19

داده‌کاوی

طبقه‌بندی

الگوریتم روابط اجتماعی درختان

نایو بیز

موضوعات

هوش مصنوعی

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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