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.
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