Artificial intelligence in pathology: from image analysis to clinical decision support

Artificial intelligence is transforming pathology by enhancing diagnostic precision and supporting clinical decision-making.Its application often involves digital imaging and machine learning to analyse whole slide imaging (WSI) data.AI algorithms can detect cellular abnormalities, classify cancers, and predict outcomes more accurately than traditional approaches, enabling faster and more reliable diagnoses.This is especially valuable in cancer pathology, where early detection and precise classification are critical for effective treatment.Despite its benefits, AI faces challenges, including limited data availability, algorithm validation, and seamless integration into clinical workflows.This paper reviews current literature on AI's role in pathology, highlighting its capacity to improve diagnostic accuracy and efficiency while examining barriers to broader adoption.As technology advances, AI holds substantial promise to revolutionize the discipline, ultimately enhancing patient care and reducing diagnostic errors.By addressing challenges, AI-driven pathology may soon become a cornerstone of modern healthcare.

Authors

Publication Details

Journal
Medical Studies
Published
2025-01-01
DOI
https://doi.org/10.5114/ms.2025.154278
Primary Topic
AI in cancer detection
Type
article
Field-Weighted Citation Impact
0.00
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Artificial intelligence in pathology: from image analysis to clinical decision support

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Artificial intelligence in pathology: from image analysis to clinical decision support

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article en

Abstract

Artificial intelligence is transforming pathology by enhancing diagnostic precision and supporting clinical decision-making.Its application often involves digital imaging and machine learning to analyse whole slide imaging (WSI) data.AI algorithms can detect cellular abnormalities, classify cancers, and predict outcomes more accurately than traditional approaches, enabling faster and more reliable diagnoses.This is especially valuable in cancer pathology, where early detection and precise classification are critical for effective treatment.Despite its benefits, AI faces challenges, including limited data availability, algorithm validation, and seamless integration into clinical workflows.This paper reviews current literature on AI's role in pathology, highlighting its capacity to improve diagnostic accuracy and efficiency while examining barriers to broader adoption.As technology advances, AI holds substantial promise to revolutionize the discipline, ultimately enhancing patient care and reducing diagnostic errors.By addressing challenges, AI-driven pathology may soon become a cornerstone of modern healthcare.

Medical Studies
Openalex Percentile: Top 87%
AI in cancer detection
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