Large language models generating synthetic clinical datasets: a feasibility and comparative analysis with real-world perioperative data
BackgroundClinical data is instrumental to medical research, machine learning (ML) model development, and advancing surgical care, but access is often constrained by privacy regulations and missing data. Synthetic data offers a promising solution to preserve privacy while enabling broader data acces...
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Main Authors: | Austin A. Barr, Joshua Quan, Eddie Guo, Emre Sezgin |
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Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2025-02-01
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Series: | Frontiers in Artificial Intelligence |
Subjects: | |
Online Access: | https://www.frontiersin.org/articles/10.3389/frai.2025.1533508/full |
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