Potentials and Limitations of Large Language Models in the Processing of Routine Clinical Data in Spine Surgery

GFO Kliniken Rhein-Berg0 个研究点目标入组 200 人开始时间: 2026年7月15日最近更新: 2026年8月3日

适应症

试验速览

暂无简介。

•Patients who underwent spinal surgery, particularly for degenerative or traumatic spinal disorders.
•Availability of a complete written operative report generated as part of routine clinical care.
•Availability of sufficient clinical information, including:
•preoperative diagnosis and surgical indication, clinical examination findings,
•relevant comorbidities, preoperative clinical documentation, and
•preoperative imaging studies (e.g., CT, MRI, or radiographs) that were used for routine clinical decision-making.

•Missing or incomplete operative reports.
•Insufficient clinical documentation preventing a valid assessment of the LLM-generated outputs (e.g., missing preoperative diagnosis, imaging studies, or clinical documentation).
•Missing or insufficient clinical or radiological source data required for the predefined study objectives.
•Records containing substantial documentation errors or inconsistencies that preclude reliable evaluation of the generated outputs.
•Non-pseudonymized datasets or datasets that cannot be processed in accordance with applicable data protection regulations.
•Documents not generated as part of routine clinical care (e.g., documents created exclusively for research purposes).

发起方

GFO Kliniken Rhein-Berg