مجله علمی پزشکی جندی شاپور

مجله علمی پزشکی جندی شاپور

پیشرفتها و چالش‌های هوش مصنوعی در تشخیص کبد چرب غیرالکلی: مرور نظام‌مند

نوع مقاله : مروری

نویسندگان
1 کارشناسی ارشد، گروه آمار، دانشگاه علامه طباطبایی، تهران، ایران.
2 کمیته تحقیقات دانشجویی، دانشجوی کارشناسی ارشد انفورماتیک پزشکی، گروه فناوری اطلاعات و مدیریت سلامت، دانشکده علوم پزشکی پیراپزشکی، دانشگاه علوم پزشکی شهید بهشتی، تهران، ایران.
3 گروه فناوری اطلاعات سلامت، دانشکده علوم پزشکی وابسته، دانشگاه علوم پزشکی شاهرود، شاهرود، ایران
10.32592/jsmj.24.1.1
چکیده
زمینه و هدف کبد چرب غیرالکلی یکی از شایع‌ترین بیماری‌ها در جهان است. در صورت تشخیص ندادن و درمان نشدن، بیماری تشدید می‌شود. درحال‌حاضر بیوپسی کبد روش استاندارد برای تشخیص بیماری است که محدودیت‌های بسیاری دارد. الگوریتم‌های هوش مصنوعی می‌توانند از معیارهای بالینی و تصویربرداری برای تشخیص کبد چرب استفاده کنند. در این مطالعه به بررسی روش‌های تشخیص به کمک هوش مصنوعی پرداخته شده است.
روش بررسی مطالعهی حاضر مرور سیستماتیک استفاده از هوش مصنوعی برای تشخیص بیماری کبد چرب است. در مرحله‌ی اول، مقالات در پایگاه‌های داده‌ی استنادی با معیارهای تعیین‌شده انتخاب و سپس براساس الگوریتم استفاده‌شده، نوع داده‌های مورد مطالعه، حضور متخصص بالینی و ارزیابی بالینی بررسی شدند. جهت سنجش عملکرد الگوریتم‌های هوش مصنوعی، از معیارهای مختلف ارزیابی استفاده شده است.
یافته‌ها پژوهشگران پس از بررسی مشاهده کردند که تشخیص در 42 درصد از مقالات با کمک پردازش تصویر و 58 درصد با کمک بیومارکرها بوده و 84 درصد از مقالات، پزشک متخصص حضور داشته است و تقریباً در هیچ مطالعه‌ای از ارزیابی بالینی استفاده نشده است و بیشتر، از الگوریتم‌های جعبه‌ی سیاه هستند. همچنین نتایج آزمون T-TEST آشکار کرد که عملکرد هوش مصنوعی در دو روش تشخیصی تفاوت زیادی با یکدیگر ندارد.
نتیجه‌گیری استفاده از هوش مصنوعی برای تشخیص بیماری کبد چرب کمک بسیار زیادی می‌کند؛ ولی عدم ارزیابی بالینی و استفاده از الگوریتم‌های جعبه‌ی سیاه، چالشی است که استفاده از الگوریتم‌ها با آن مواجه است و محدودیتهای قابل‌توجهی برای کاربرد فعلی هوش مصنوعی در محیطهای بالینی ایجاد می‌کند.
کلیدواژه‌ها
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