Koronar arteriyalarning MSKT tahlilda sun’iy intellektdan foydalanish
Kalit so'zlar:
Koronar arteriyalar, MSKT, sun‘iy intellekt, kompyuter tomografiya, stenoz, ateroskleroz, diagnostika, prognoz, yurak-qon tomir kasalliklariAnnotatsiya
Ushbu maqolada koronar arteriyalarning multispiral kompyuter tomografiyasi (MSKT) tasvirlarini tahlil qilishda sun‘iy intellekt (SI) texnologiyalarining zamonaviy imkoniyatlari o'rganildi. So'nggi tadqiqotlar shuni ko'rsatadiki, SI yordamida koronar arteriyalarda stenoz darajasini aniqlash, aterosklerotik plaklarni baholash hamda yurak-qon tomir asoratlarini prognoz qilish imkoniyati sezilarli darajada yaxshilanadi. Tahlillar natijasida aniqlanishicha, SI algoritmlari diagnostik aniqlikni oshiradi, shifokorlar ishini tezlashtiradi va individual davolash strategiyasini ishlab chiqishda muhim ahamiyat kasb etadi.
Foydalanilgan adabiyotlar
1. Dey D, Slomka PJ, Leeson P, et al. Artificial intelligence in coronary CT angiography. J Am Coll Cardiol. 2025;85(4):345–358. https://pubmed.ncbi.nlm.nih.gov/40576859
2. Knuuti J, Bax JJ, Saraste A, et al. Coronary CT angiography evaluation with artificial intelligence for individualized treatment. Nat Rev Cardiol. 2026;23(1):15–28. https://pubmed.ncbi.nlm.nih.gov/40751112/
3. van Rosendael AR, Bax AM, Smit JM, et al. Artificial intelligence in CT angiography for detection of coronary stenosis. Eur Heart J Cardiovasc Imaging. 2025;26(2):210–220. https://pubmed.ncbi.nlm.nih.gov/40234162/
4. Motwani M, Dey D, Berman DS, et al. Machine learning for prediction of major adverse cardiovascular events using coronary CT angiography. JACC Cardiovasc Imaging. 2025;18(3):400–412. https://pubmed.ncbi.nlm.nih.gov/39389811/
5. Commandeur F, Goeller M, Razipour A, et al. Prognostic value of coronary CTA-based artificial intelligence plaque quantification. Radiology. 2025;305(1):98–107. https://pubmed.ncbi.nlm.nih.gov/41075372/
6. Lin A, Kolossváry M, Motwani M, et al. AI-enabled coronary plaque analysis and prediction of acute coronary syndrome. Eur Heart J. 2026;47(3):300–312. https://pubmed.ncbi.nlm.nih.gov/41346196/