How does AI perform compared to human expert panels in medical Delphi studies? A pilot study through the lens of pathology

Background: Since their inception, Delphi studies have been a key part of medical literature. They consist of an expert panel tasked with coming to consensus on answers to various questions where obtaining objective results is difficult or impossible, with ranked responses based on a Likert scale. T...

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主要な著者:	Joshua Pantanowitz, Christopher D. Manko, John Majewski, M. Alvaro Berbís, Alton B. Farris, III, Aly Karsan, Andrey Bychkov, Antonio Luna, Bethany Williams, Brett Delahunt, Catarina Eloy, David S. McClintock, Eva Hollemans, J. Mark Tuthill, Jeroen Van der Laak, Jerome Y. Cheng, Jochen K. Lennerz, John H. Sinard, Jose Aneiros-Fernandez, Julien Calderaro, Kenneth A. Iczkowski, Lars Egevad, Mark Kriegsmann, Markus D. Herrmann, Mohamed E. Salama, Raimundo Garcia Del Moral, S. Joseph Sirintrapun, Colleen Vrbin, Liron Pantanowitz, Jeanne Shen, Hooman Rashidi
フォーマット:	Artigo
言語:	Inglês
出版事項:	Elsevier 2026-04-01
シリーズ:	Journal of Pathology Informatics
主題:	Delphi study Artificial intelligence Large language model Pathology Medicine Temperature setting
オンライン･アクセス:	http://www.sciencedirect.com/science/article/pii/S2153353926001197
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