Harnessing the Power of Generative Artificial Intelligence in Pathology Education.

Autor:	Cecchini MJ; From the Department of Pathology and Laboratory Medicine, Western University and London Health Sciences Centre, London, Ontario, Canada (Cecchini)., Borowitz MJ; the Department of Pathology, Johns Hopkins Medical Institutions, Baltimore, Maryland (Borowitz)., Glassy EF; Affiliated Pathologists Medical Group, Rancho Dominguez, California (Glassy)., Gullapalli RR; the Department of Pathology, Department of Chemical and Biological Engineering, University of New Mexico, Albuquerque (Gullapalli)., Hart SN; the Division of Computational Pathology and AI, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota (Hart)., Hassell LA; the Department of Pathology, University of Oklahoma Health Sciences Center, Oklahoma City (Hassell)., Homer RJ; the Department of Pathology, Yale School of Medicine, New Haven, Connecticut (Homer)., Jackups R Jr; the Department of Pathology, Washington University in St Louis School of Medicine, St Louis, Missouri (Jackups)., McNeal JL; Education Program Design, College of American Pathologists, Northfield, Illinois (McNeal)., Anderson SR; the Department of Pathology and Laboratory Medicine, University of Vermont Medical Center, Burlington (Anderson).
Jazyk:	angličtina
Zdroj:	Archives of pathology & laboratory medicine [Arch Pathol Lab Med] 2024 Sep 30. Date of Electronic Publication: 2024 Sep 30.
DOI:	10.5858/arpa.2024-0187-RA
Abstrakt:	Context.—: Generative artificial intelligence (AI) technologies are rapidly transforming numerous fields, including pathology, and hold significant potential to revolutionize educational approaches. Objective.—: To explore the application of generative AI, particularly large language models and multimodal tools, for enhancing pathology education. We describe their potential to create personalized learning experiences, streamline content development, expand access to educational resources, and support both learners and educators throughout the training and practice continuum. Data Sources.—: We draw on insights from existing literature on AI in education and the collective expertise of the coauthors within this rapidly evolving field. Case studies highlight practical applications of large language models, demonstrating both the potential benefits and unique challenges associated with implementing these technologies in pathology education. Conclusions.—: Generative AI presents a powerful tool kit for enriching pathology education, offering opportunities for greater engagement, accessibility, and personalization. Careful consideration of ethical implications, potential risks, and appropriate mitigation strategies is essential for the responsible and effective integration of these technologies. Future success lies in fostering collaborative development between AI experts and medical educators, prioritizing ongoing human oversight and transparency to ensure that generative AI augments, rather than supplants, the vital role of educators in pathology training and practice. Competing Interests: The authors have no relevant financial interest in the products or companies described in this article. (© 2024 College of American Pathologists.)
Databáze:	MEDLINE
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