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Artificial Intelligence in Pathology: Past, Present, and Future Perspectives

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Názov: Artificial Intelligence in Pathology: Past, Present, and Future Perspectives
Autori: Isma Balaj, Sibora Bërdica, Teona Bushati
Zdroj: Albanian Journal of Trauma and Emergency Surgery, Vol 9, Iss 2 (2025)
Informácie o vydavateľovi: Albanian Society for Trauma and Emergency Surgery, 2025.
Rok vydania: 2025
Predmety: RD1-811, RC86-88.9, immunohistochemistry, histopathology, Surgery, Medical emergencies. Critical care. Intensive care. First aid, digital pathology, Artificial intelligence (AI), tumor grading
Popis: 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.
Druh dokumentu: Article
ISSN: 2616-4922
2521-8778
DOI: 10.32391/ajtes.v9i2.449
Prístupová URL adresa: https://doaj.org/article/7c5d24a2e3b14a10985a63eb67f6e881
Rights: CC BY NC
Prístupové číslo: edsair.doi.dedup.....9c2d3be3eb091f28989a1f3afa7efc6c
Databáza: OpenAIRE
Popis
Abstrakt: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.
ISSN:26164922
25218778
DOI:10.32391/ajtes.v9i2.449