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The emerging role of generative artificial intelligence in transplant medicine

Authors :
Deeb, Maya
Gangadhar, Anirudh
Rabindranath, Madhumitha
Rao, Khyathi
Brudno, Michael
Sidhu, Aman
Wang, Bo
Bhat, Mamatha
Source :
American journal of transplantation; October 2024, Vol. 24 Issue: 10 p1724-1730, 7p
Publication Year :
2024

Abstract

Generative artificial intelligence (AI), a subset of machine learning that creates new content based on training data, has witnessed tremendous advances in recent years. Practical applications have been identified in health care in general, and there is significant opportunity in transplant medicine for generative AI to simplify tasks in research, medical education, and clinical practice. In addition, patients stand to benefit from patient education that is more readily provided by generative AI applications. This review aims to catalyze the development and adoption of generative AI in transplantation by introducing basic AI and generative AI concepts to the transplant clinician and summarizing its current and potential applications within the field. We provide an overview of applications to the clinician, researcher, educator, and patient. We also highlight the challenges involved in bringing these applications to the bedside and need for ongoing refinement of generative AI applications to sustainably augment the transplantation field.

Details

Language :
English
ISSN :
16006135 and 16006143
Volume :
24
Issue :
10
Database :
Supplemental Index
Journal :
American journal of transplantation
Publication Type :
Periodical
Accession number :
ejs66670116
Full Text :
https://doi.org/10.1016/j.ajt.2024.06.009