“RADIOLOGIYADA SUN’IY INTELLEKT: MRT VA KT TASVIRLARINI MASHINAVIY O‘RGANISH IMKONIYATLARI”
Jild 5 son 13 (2026): Zamonaviy dunyoda ilm-fan va texnologiya 4-5
Annotatsiya
Ushbu tezisda sun’iy intellekt (AI), mashinaviy o‘rganish (ML) va chuqur o‘rganish (DL) texnologiyalari, ayniqsa Konvolyutsion Neyron Tarmoqlari (CNN), radiologiyada MRT va KT tasvirlarini qayta ishlash va patologik o‘zgarishlarni aniqlashda qo‘llanilishi ko‘rib chiqildi. Tadqiqot natijalari shuni ko‘rsatdiki, AI yordamida tasvirlar tez va aniq tahlil qilinib, diagnostika aniqligi oshadi va ish jarayoni optimallashtiriladi.
Kalit soʻzlar:
Iqtiboslar
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Ali S.S.A., Memon K., Yahya N., et al. Deep learning frameworks for MRI based diagnosis of neurological disorders: a systematic review and meta analysis. Artificial Intelligence Review. 2025. Systematic review of DL frameworks for MRI diagnostics of neurological disorders. https://link.springer.com/article/10.1007/s10462-025-11146-5
Bernal J., Kushibar K., Asfaw D.S., Valverde S., et al. Deep convolutional neural networks for brain image analysis on magnetic resonance imaging: a review. arXiv preprint. 2017. Classic foundational overview of CNN for MRI analysis. https://arxiv.org/abs/1712.03747
Chikhacheva Y.G., Miruk A.K., Lomonosova A.V., Kozlova A.A. Искусственный интеллект в медицине: обзор текущей ситуации и тенденции. Medico Biological Sciences Journal. 2024;2(2). Overview of AI trends in medical practice. https://medbio.cifra.science/archive/2-2-2024-september/10.60797/BMED.2024.2.4
Mutasa S., Sun S., Ha R. Understanding artificial intelligence based radiology studies: CNN architecture. Clin. Imaging. 2021;80:72–76. Analysis of CNN architecture applications in radiology. https://pmc.ncbi.nlm.nih.gov/articles/PMC11394591
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