TY - JOUR
T1 - Organizational preparedness for the use of large language models in pathology informatics
AU - Hart, Steven N.
AU - Hoffman, Noah G.
AU - Gershkovich, Peter
AU - Christenson, Chancey
AU - McClintock, David S.
AU - Miller, Lauren J.
AU - Jackups, Ronald
AU - Azimi, Vahid
AU - Spies, Nicholas
AU - Brodsky, Victor
N1 - Publisher Copyright:
© 2023 The Authors
PY - 2023/1
Y1 - 2023/1
N2 - In this paper, we consider the current and potential role of the latest generation of Large Language Models (LLMs) in medical informatics, particularly within the realms of clinical and anatomic pathology. We aim to provide a thorough understanding of the considerations that arise when employing LLMs in healthcare settings, such as determining appropriate use cases and evaluating the advantages and limitations of these models. Furthermore, this paper will consider the infrastructural and organizational requirements necessary for the successful implementation and utilization of LLMs in healthcare environments. We will discuss the importance of addressing education, security, bias, and privacy concerns associated with LLMs in clinical informatics, as well as the need for a robust framework to overcome regulatory, compliance, and legal challenges.
AB - In this paper, we consider the current and potential role of the latest generation of Large Language Models (LLMs) in medical informatics, particularly within the realms of clinical and anatomic pathology. We aim to provide a thorough understanding of the considerations that arise when employing LLMs in healthcare settings, such as determining appropriate use cases and evaluating the advantages and limitations of these models. Furthermore, this paper will consider the infrastructural and organizational requirements necessary for the successful implementation and utilization of LLMs in healthcare environments. We will discuss the importance of addressing education, security, bias, and privacy concerns associated with LLMs in clinical informatics, as well as the need for a robust framework to overcome regulatory, compliance, and legal challenges.
KW - Artificial intelligence
KW - Best practices
KW - Large language models
UR - http://www.scopus.com/inward/record.url?scp=85173991973&partnerID=8YFLogxK
U2 - 10.1016/j.jpi.2023.100338
DO - 10.1016/j.jpi.2023.100338
M3 - Review article
C2 - 37860713
AN - SCOPUS:85173991973
SN - 2229-5089
VL - 14
JO - Journal of Pathology Informatics
JF - Journal of Pathology Informatics
M1 - 100338
ER -