UTOMATED DIAGNOSTICS BASED ON ARTIFICIAL INTELLIGENCE: MEDICAL IMAGE ANALYSIS AND EARLY DIAGNOSIS TECHNOLOGIES

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Originally published in MEDICINE, PEDAGOGY AND TECHNOLOGY: THEORY AND PRACTICE; Vol. 3 No. 10 (2025): MEDICINE, PEDAGOGY AND TECHNOLOGY: THEORY AND PRACTICE; 177-181.

Turdimuratov, Baxtiyor and Boymurodova, Mohlaroyim (2025) UTOMATED DIAGNOSTICS BASED ON ARTIFICIAL INTELLIGENCE: MEDICAL IMAGE ANALYSIS AND EARLY DIAGNOSIS TECHNOLOGIES. MEDICINE, PEDAGOGY AND TECHNOLOGY: THEORY AND PRACTICE; Vol. 3 No. 10 (2025): MEDICINE, PEDAGOGY AND TECHNOLOGY: THEORY AND PRACTICE; 177-181.

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Abstract

This article examines the application of artificial intelligence (AI) and deep learning methods in automated medical diagnostics, with a particular focus on radiology, medical imaging, and early cancer detection. AI-based image analysis significantly increases diagnostic accuracy, reduces human error, and enables the early identification of life-threatening diseases. Convolutional neural networks (CNNs), computer vision algorithms, and automated decision-support systems are analyzed in detail. The results show that AI-assisted diagnostics can improve detection rates of lung, breast, and colorectal cancers and serve as an effective tool for radiologists.

Item Type: Article
Additional Information: Imported from Medicine, Pedagogy and Technology: Theory and Practice
SWORD Depositor: Admin User
Depositing User: Admin User
Date Deposited: 10 Oct 2026 21:09
Last Modified: 10 Oct 2026 21:09
URI: https://universalpublishings.uz/id/eprint/20905

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