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Artificial Intelligence in Pathology: Bridging the Gap Between Technology and Diagnostics

Sneha Chavarkar.



Abstract
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In recent years, there has been a considerable increase in the development and application of Artificial Intelligence (AI) tools in pathology. In the current era of precision medicine, computational pathology (CPATH) and AI tools will drastically transform pathology services. Despite tremendous success in the development of AI tools, there exists a wide gap between the research and its clinical application in pathology. This article explores how Artificial Intelligence (AI) revolutionizes pathology by bridging the gap between traditional diagnostic methods and advanced technological innovations. It seeks to highlight the potential of AI to enhance diagnostic accuracy, efficiency, and precision while addressing the challenges and opportunities for integrating AI into modern pathology practices. The author conducted a PubMed search for articles published between January 1990 and August 2024. Terms like “AI artificial intelligence,” “deep learning,” and “machine learning” were searched using MeSH (Medical Subject Headings). Currently, AI plays a supportive role in pathology. It can also help to prognosticate malignancies. Supportive data indicates that with the aid of AI, pathologists can reach diagnosis swiftly and with more accuracy. We concluded that by bridging the gap between traditional diagnostic practices and cutting-edge technology, AI will help pathologists contribute more efficiently to precision medicine. While challenges like data quality, regulatory compliance, and ethical concerns remain, the future of pathology depends on seamless collaboration between AI tools and human expertise.

Key words: Artificial intelligence, Deep learning, Machine learning, Neural networks computer, Algorithm







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0102030405
2026

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