Artificial Intelligence in Pathology: Past, Present, and Future Perspectives
Introduction: Artificial intelligence (AI) is at the forefront of modern technology, with emerging applications in the healthcare sector now gaining recognition. Pathology is anticipated to be a key area where the impact of AI will be substantial. As more laboratories transition to digital patholog...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Albanian Society for Trauma and Emergency Surgery
2025-07-01
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| Series: | Albanian Journal of Trauma and Emergency Surgery |
| Subjects: | |
| Online Access: | https://journal.astes.org.al/AJTES/index.php/AJTES/article/view/449 |
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| Summary: | Introduction: Artificial intelligence (AI) is at the forefront of modern technology, with emerging applications in the healthcare sector now gaining recognition. Pathology is anticipated to be a key area where the impact of AI will be substantial. As more laboratories transition to digital pathology, this will create the essential infrastructure needed to implement these tools, making their application a reality in diagnostic practice. The potential of AI in pathology lies in developing image analysis tools that can support diagnosis or generate new insights into disease biology, beyond what a human observer can achieve. Examples currently exist providing diagnostic support for a limited but growing number of applications, such as tumor detection, automated tumor grading, immunohistochemistry scoring, and predicting mutation status. Several challenges remain, including the validation and establishment of a regulatory framework for these tools, as well as the ethical implications of AI in pathology. These include concerns about patient privacy and consent, along with the potential for AI to worsen existing healthcare disparities. In this article, we offer an overview of AI in histopathology, discuss its possible workflow applications, and highlight significant examples of AI's potential impact in clinical practice. We also explore considerations for implementing AI in practice.
Conclusion: There has been a significant increase in the development and application of AI tools, including image-based algorithms, in pathology services, and they are expected to dominate the field in the coming years. The implementation of computational pathology and the use of pathology-related AI tools can be viewed as a paradigm shift that will transform the management of pathology services. While AI will undoubtedly enhance the efficiency of pathology services, it is crucial to recognize that it will not replace the role of pathologists. Instead, it will augment their capabilities, enabling them better to meet the demands of this era of precision medicine.
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| ISSN: | 2521-8778 2616-4922 |