Frontiers | Large language models generating synthetic clinical datasets: a feasibility and comparative analysis with real-world perioperative data
1 Cumming School of Medicine, University of Calgary, Calgary, AB, Canada 2 The Abigail Wexner Research Institute, Nationwide Children’s Hospital, Columbus, OH, United States 3 Department of Pediatrics, The Ohio State University College of Medicine, Columbus, OH, United States Background: Clinical data is instrumental to medical research, machine learning (ML) model development, an d advancing surgical care, but access is often constrained by privacy regulations and missing data. Synthetic data offers a
