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 |
