TIBBIYOTDA SUN’IY INTELLEKT VA EXPLAINABLE AI. KASALLIKLARNI PROGNOZLASH VA KLINIK QAROR QABUL QILISHDAGI SAMARADORLIK
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Ushbu maqolada sun’iy intellekt (SI) va ayniqsa tushuntiriladigan sun’iy intellekt (Explainable Ushbu maqola sun’iy intellekt (SI)
va Explainable AI (XAI)ning tibbiyotdagi kasalliklarni prognoz qilishdagi qo‘llanilishi, klassifikatsiya modellarining ishlash
tamoyillari, SHAP va LIME metodlari orqali tushuntirish, klinik qaror qabul qilishdagi samaradorlik va XAI natijalari bilan bog‘liq
amaliy cheklovlarni yoritadi. Maqolada elektron sog‘liqni saqlash yozuvlari (EHR) va tibbiy tasvirlar asosida ishlovchi AI tizimlari,
ularning aniqligi, sezgirligi va shaffoflikka bo‘lgan ehtiyoji, shuningdek, model natijalarini vizualizatsiya qilish orqali klinik
ishonchlilikni oshirish usullari ko‘rib chiqilgan.
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Sustainable Development in Computer Science Engineering, 2020+. journals.threws.com
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Risk Assessment. Digital Transformation and Artificial Intelligence, 2025, 3(1), 191–195. dtai.tsue.uz
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European Journal of Public Health, 2025, 35(Suppl_4). DOI:10.1093/eurpub/ckaf161.1294. OUP Academic
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Computations, Information and Manufacturing, 2024, 4(1). journals.gaftim.com
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future research directions. BMC Medical Informatics and Decision Making, 2025, 25:110. BioMed Central
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(IJSAT), 2025. ijsat.org
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A Comparative Study of ML and Explainability Analysis. arxiv preprint, 2025
11. AXMADIYEV, N. (2025). PHILOSOPHICAL AND METHODOLOGICAL FOUNDATIONS OF SOCIETY DEVELOPMENT. «ACTA NUUz», 1(1.12), 73–75. Retrieved from https://journalsnuu.uz/index.php/actanuuz/article/view/10257
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