THE ROLE OF DIGITAL HISTOLOGY AND ARTIFICIAL INTELLIGENCE TECHNOLOGIES IN MODERN PATHOLOGY
DOI:
https://doi.org/10.55640/Keywords:
Digital histology · Digital pathology · Artificial intelligence · Deep learning · Convolutional neural network · Whole Slide Imaging · Oncohistology · SegmentationAbstract
This article provides a scientific examination of the significance of digital histology (digital pathology) and artificial intelligence (AI) technologies in the contemporary diagnostic process. The study highlights the capabilities of automatic segmentation and classification of histological images facilitated by Whole Slide Imaging (WSI) systems, deep learning algorithms, and convolutional neural networks (CNN). The integration of these technologies into clinical practice, their principal advantages, and existing limitations are comprehensively discussed. Findings indicate that AI-assisted diagnostic tools substantially enhance accuracy, reproducibility, and efficiency across a range of oncological and pathological conditions.
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Authors retain the copyright of their manuscripts, and all Open Access articles are disseminated under the terms of the Creative Commons Attribution License 4.0 (CC-BY), which licenses unrestricted use, distribution, and reproduction in any medium, provided that the original work is appropriately cited. The use of general descriptive names, trade names, trademarks, and so forth in this publication, even if not specifically identified, does not imply that these names are not protected by the relevant laws and regulations.
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