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Biomedical Reports
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Print ISSN: 2049-9434 Online ISSN: 2049-9442
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October-2026 Volume 25 Issue 4

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International Journal of Molecular Medicine

International Journal of Molecular Medicine

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Covers molecular medicine topics such as pharmacology, pathology, genetics, neuroscience, infectious diseases, molecular cardiology, and molecular surgery.

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Oncology Reports is an international journal devoted to fundamental and applied research in Oncology.

Experimental and Therapeutic Medicine

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Experimental and Therapeutic Medicine is an international journal devoted to laboratory and clinical medicine.

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Oncology Letters is an international journal devoted to Experimental and Clinical Oncology.

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Review Open Access

Artificial intelligence in digital pathology diagnosis and analysis: Technologies, clinical integration, and future prospects (Review)

  • Authors:
    • Abdul-Mohsen Alhejaily
    • Doaa Alghamdi

  • View Affiliations / Copyright

    Affiliations: Scientific Publication Support Unit and Academic Operations Administration, King Fahad Medical City, Riyadh Second Health Cluster, Riyadh 11525, Saudi Arabia, Department of Anatomical Pathology, King Fahad Medical City, Riyadh Second Health Cluster, Riyadh 11525, Saudi Arabia
    Copyright: © Alhejaily et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
  • Article Number: 109
    |
    Published online on: August 3, 2026
       https://doi.org/10.3892/br.2026.2182
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Abstract

The integration of artificial intelligence (AI) into digital pathology is perhaps the most revolutionary leap forward in modern diagnostic medicine. The present review analyzes the existing context of AI pathology systems, particularly diagnostic precision, clinical validation, and technical systems such as convolutional neural networks and transformers and discusses the integration challenge in clinical workflows for these systems. AI systems have achieved pathologist‑level performance in controlled settings, including diagnostic accuracy >99% and area under the receiver operating characteristic curve values exceeding 0.97. However, translating research into clinical adoption is riddled with several challenges attributable to computational requirements, data standardization issues, regulatory hurdles and limitations in generalizability. Moreover, Vision Transformers are widely popular as powerful alternatives to conventional convolutional models, delivering high performance in certain domains while also imposing a novel computational burden. Overcoming these challenges is a prerequisite for the successful integration of AI into pathology practice and the realization of its full diagnostic potential.

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Copy and paste a formatted citation
Spandidos Publications style
Alhejaily A and Alghamdi D: Artificial intelligence in digital pathology diagnosis and analysis: Technologies, clinical integration, and future prospects (Review). Biomed Rep 25: 109, 2026.
APA
Alhejaily, A., & Alghamdi, D. (2026). Artificial intelligence in digital pathology diagnosis and analysis: Technologies, clinical integration, and future prospects (Review). Biomedical Reports, 25, 109. https://doi.org/10.3892/br.2026.2182
MLA
Alhejaily, A., Alghamdi, D."Artificial intelligence in digital pathology diagnosis and analysis: Technologies, clinical integration, and future prospects (Review)". Biomedical Reports 25.4 (2026): 109.
Chicago
Alhejaily, A., Alghamdi, D."Artificial intelligence in digital pathology diagnosis and analysis: Technologies, clinical integration, and future prospects (Review)". Biomedical Reports 25, no. 4 (2026): 109. https://doi.org/10.3892/br.2026.2182
Copy and paste a formatted citation
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Spandidos Publications style
Alhejaily A and Alghamdi D: Artificial intelligence in digital pathology diagnosis and analysis: Technologies, clinical integration, and future prospects (Review). Biomed Rep 25: 109, 2026.
APA
Alhejaily, A., & Alghamdi, D. (2026). Artificial intelligence in digital pathology diagnosis and analysis: Technologies, clinical integration, and future prospects (Review). Biomedical Reports, 25, 109. https://doi.org/10.3892/br.2026.2182
MLA
Alhejaily, A., Alghamdi, D."Artificial intelligence in digital pathology diagnosis and analysis: Technologies, clinical integration, and future prospects (Review)". Biomedical Reports 25.4 (2026): 109.
Chicago
Alhejaily, A., Alghamdi, D."Artificial intelligence in digital pathology diagnosis and analysis: Technologies, clinical integration, and future prospects (Review)". Biomedical Reports 25, no. 4 (2026): 109. https://doi.org/10.3892/br.2026.2182
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