This research explores using GPT-4o to generate synthetic neurosurgical data to address challenges in accessing real-world clinical data for research.

• Overcomes limitations of real medical data including small sample sizes and strict privacy regulations
• Enables researchers to create synthetic alternatives to sensitive patient information
• Provides a benchmark for evaluating the capability of LLMs in generating realistic medical data
• Offers a potential solution to accelerate neurosurgical research without compromising patient privacy

This advancement matters for medicine by potentially democratizing access to high-quality neurosurgical data, enabling broader research participation, and accelerating development of treatment protocols without exposing protected health information.

Zero-shot generation of synthetic neurosurgical data with large language models