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Abstract
Qandli diabet retinopatiyasi (QDR) butun dunyoda mehnatga layoqatli aholida qaytarilmas ko‘rlikning asosiy sabablaridan biri hisoblanadi. Jahon sog‘liqni saqlash tashkiloti ma’lumotlariga ko‘ra, diabet bilan kasallangan bemorlar sonining ortib borishi diabetik retinopatiya uchrash chastotasining ham keskin oshishiga olib kelmoqda. Kasallikning dastlabki bosqichlarida klinik belgilar kam namoyon bo‘lishi sababli ko‘plab bemorlar kech bosqichlarda shifokorga murojaat qiladi, bu esa davolash samaradorligini pasaytiradi.
Mazkur tadqiqotning maqsadi qandli diabet retinopatiyasini erta aniqlashda sun’iy intellekt texnologiyalarining diagnostik imkoniyatlarini baholash, OCT (Optical Coherence Tomography), OCT-Angiography va fundus fotografiyasi natijalari asosida individual xavf prognozini ishlab chiqish hamda yangi skrining algoritmini taklif etishdan iborat.
2023–2026-yillar davomida Respublikaning uchta ixtisoslashtirilgan oftalmologiya markazida davolangan 548 nafar qandli diabet bilan kasallangan bemor klinik kuzatuvga olindi. Tadqiqot davomida bemorlarning fundus tasvirlari, OCT va OCTA ko‘rsatkichlari chuqur o‘rganildi. Sun’iy intellekt asosidagi konvolyutsion neyron tarmoqlar (CNN) yordamida retinal mikroanevrizmalar, qon quyilishlar, qattiq ekssudatlar va neovaskulyarizatsiya belgilarini avtomatik aniqlash amalga oshirildi.
Natijalarga ko‘ra, sun’iy intellekt asosidagi diagnostika tizimi diabetik retinopatiyani aniqlashda 97,8 % sezuvchanlik, 96,9 % spetsifiklik va 97,3 % umumiy diagnostik aniqlik ko‘rsatkichlarini namoyon etdi. An’anaviy oftalmoskopik tekshiruv bilan taqqoslaganda, kasallikning erta bosqichlarini aniqlash samaradorligi 18,6 % ga, skrining o‘tkazish tezligi esa 61,4 % ga oshgani kuzatildi.
Taklif etilgan yangi sun’iy intellekt asosidagi skrining algoritmi diabetik retinopatiyani erta bosqichlarda aniqlash, ko‘rlikning oldini olish hamda bemorlarni individual monitoring qilish imkoniyatlarini sezilarli darajada yaxshilashi aniqlandi.
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