This article analyzes the potential and effectiveness of artificial intelligence technologies in histological diagnostics. In modern medicine, histological examinations are essential for identifying diseases, particularly oncological pathologies. However, traditional diagnostic methods are often limited by their labor-intensive nature, dependence on human error, and the potential for error. Therefore, the implementation of artificial intelligence-based algorithms is a pressing issue. This article discusses methods for automatic analysis of histological images using deep learning and convolutional neural networks (CNN). The results of the study demonstrate that artificial intelligence systems can improve diagnostic accuracy, reduce analysis time, and optimize physician workflow. The advantages and limitations of this technology are also discussed.

Artificial intelligence, histological diagnostics, digital pathology, neural networks, deep learning, convolutional neural networks (CNN), medical image analysis, automated diagnostics.

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