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زاهدیان نژاد, محمود, مهرآیین, محمد, باقری, روح الله, طباطبایی, سید محمد. (1405). ارزیابی جامع مدل‌های یادگیری گروهی (EL) در مدیریت بیماری‌های قلبی عروقی: رویکردی فراترکیب. سامانه مدیریت نشریات علمی, 15(55), 39-126. doi: 10.22054/ims.2025.86650.2638
محمود زاهدیان نژاد; محمد مهرآیین; روح الله باقری; سید محمد طباطبایی. "ارزیابی جامع مدل‌های یادگیری گروهی (EL) در مدیریت بیماری‌های قلبی عروقی: رویکردی فراترکیب". سامانه مدیریت نشریات علمی, 15, 55, 1405, 39-126. doi: 10.22054/ims.2025.86650.2638
زاهدیان نژاد, محمود, مهرآیین, محمد, باقری, روح الله, طباطبایی, سید محمد. (1405). 'ارزیابی جامع مدل‌های یادگیری گروهی (EL) در مدیریت بیماری‌های قلبی عروقی: رویکردی فراترکیب', سامانه مدیریت نشریات علمی, 15(55), pp. 39-126. doi: 10.22054/ims.2025.86650.2638
زاهدیان نژاد, محمود, مهرآیین, محمد, باقری, روح الله, طباطبایی, سید محمد. ارزیابی جامع مدل‌های یادگیری گروهی (EL) در مدیریت بیماری‌های قلبی عروقی: رویکردی فراترکیب. سامانه مدیریت نشریات علمی, 1405; 15(55): 39-126. doi: 10.22054/ims.2025.86650.2638

ارزیابی جامع مدل‌های یادگیری گروهی (EL) در مدیریت بیماری‌های قلبی عروقی: رویکردی فراترکیب

مطالعات مدیریت کسب و کار هوشمند
مقاله 2، دوره 15، شماره 55، اردیبهشت 1405، صفحه 39-126    اصل مقاله (2.44 M)
نوع مقاله: مقاله پژوهشی
شناسه دیجیتال (DOI): 10.22054/ims.2025.86650.2638
نویسندگان
محمود زاهدیان نژاد1؛ محمد مهرآیین* 2؛ روح الله باقری3؛ سید محمد طباطبایی4
1دانشجوی دکتری رشته مدیریت فناوری اطلاعات، گروه مدیریت، دانشگاه فردوسی مشهد، مشهد، ایران
2استاد مدیریت فناوری اطلاعات،گروه مدیریت، دانشگاه فردوسی مشهد، مشهد، ایران نویسنده مسئول: mehraeen@um.ac.ir
3دانشیار مدیریت فناوری اطلاعات،گروه مدیریت، دانشگاه فردوسی مشهد، مشهد، ایران
4استادیار انفورماتیک پزشکی،گروه انفورماتیک پزشکی، دانشکده پزشکی، دانشگاه علوم پزشکی مشهد مشهد، ایران
چکیده
بیماری‌های قلبی-عروقی (CVDs) یکی از علل اصلی مرگ‌ومیر در سراسر جهان محسوب می‌شوند. افزایش داده‌های پیچیده حاصل از ابزارهای تشخیصی مانند الکتروکاردیوگرام (ECG)، چالش‌های قابل توجهی را برای پزشکان ایجاد کرده که بر دقت تشخیص و سرعت درمان تأثیر می‌گذارد. یادگیری گروهی (EL) با ترکیب مدل‌های مختلف، عملکرد بهتری را در مدیریت CVD ها ارائه می‌دهد، اما تحقیقات محدودی به صورت سیستماتیک تکنیک‌های مختلف آن را مقایسه کرده‌اند. این پژوهش با استفاده از رویکرد فراترکیب، به بررسی کاربرد مدل‌های EL در ترکیب با مدل‌های یادگیری ماشین (ML) و یادگیری عمیق (DL) می‌پردازد. هدف این مطالعه، دسته‌بندی مدل‌های EL در مدیریت CVD ها، ارزیابی عملکرد و کارایی آن‌ها در هر دسته، شناسایی مزایا و محدودیت‌ها و تحلیل نقش مهندسی ویژگی است. یافته‌های این فراترکیب نشان می‌دهد که کاربرد مدل‌های یادگیری در مدیریت CVD ها به چهار حوزه‌ی اصلی تقسیم می‌شود: پیش‌بینی، تشخیص، شناسایی و طبقه‌بندی. نتایج تأیید می‌کند که مدل‌های EL در تمام این چهار حوزه غالب هستند و کارایی آن‌ها با ادغام با تکنیک‌های ML و DL به طور قابل توجهی افزایش می‌یابد. در میان رویکردهای مختلف، مدل‌های جنگل تصادفی (RF) و الگوریتم‌های تقویت گرادیان مانند XGBoost، بیشترین فراوانی استفاده را داشته و به عنوان کارآمدترین و دقیق‌ترین مدل‌ها شناخته می‌شوند. این پژوهش با ارائه یک نمای کلی ساختاریافته، بینش‌های ارزشمندی را برای محققان و متخصصان بالینی فراهم می‌کند و چارچوبی برای به‌کارگیری مدل‌های ترکیبی جهت دستیابی به مدیریت دقیق‌تر و مؤثرتر بیماری‌های قلبی-عروقی ارائه می‌دهد.
کلیدواژه‌ها
مدیریت بیماری های قلبی عروقی (CVDs)؛ رویکرد فراترکیب؛ یادگیری گروهی (EL)؛ یادگیری ماشین (ML)؛ یادگیری عمیق (DL)
مراجع
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‌ ‌استناد به این مقاله: زاهدیان نژاد، محمود.، مهرآیین، محمد.، باقری، روح‌الله.، طباطبایی، سید محمد. (1405). ارزیابی جامع مدل‌های یادگیری گروهی (EL) در مدیریت بیماری‌های قلبی عروقی: رویکردی فراترکیب، مطالعات مدیریت کسب وکار هوشمند، 15(55)، 39-126. DOI: 10.22054/ims.2025.86650.2638

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