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Using Large Language Models to Automate Data Extraction From Surgical Pathology Reports: Retrospective Cohort Study

Using Large Language Models to Automate Data Extraction From Surgical Pathology Reports: Retrospective Cohort Study

In our preliminary trials, while combining more distinct segments could introduce variety, this approach led to a slight reduction in overall accuracy due to the introduction of less relevant or tangential information. Finally, embedding models with cosine similarity offers an efficient and robust way to evaluate how closely each segment relates to the posed question, ensuring that the selected segments are not just textually similar but semantically aligned with the user’s query.

Denise Lee, Akhil Vaid, Kartikeya M Menon, Robert Freeman, David S Matteson, Michael L Marin, Girish N Nadkarni

JMIR Form Res 2025;9:e64544

Quantifying Public Engagement With Science and Malinformation on COVID-19 Vaccines: Cross-Sectional Study

Quantifying Public Engagement With Science and Malinformation on COVID-19 Vaccines: Cross-Sectional Study

An exception was made for a tweet authored by Robert F Kennedy Jr, a public figure, as it represents a public statement made in his capacity as a public advocate. Figure 1 A depicts altmetric trends for 5 major medical journals in the decade from April 26, 2012, to April 26, 2022, for 85,529 papers, depicting growing public interest with time. It is worth noting, however, that interest is greatly skewed.

David Robert Grimes, David H Gorski

J Med Internet Res 2025;27:e64679