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Updated: Jan 11, 2026

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
Published on: December 6, 2024
Natural Language Processing and Large Language Models
Gordon C Wong1, Kevin C Chung1
1Section of Plastic Surgery, Department of Surgery, Michigan Medicine, The University of Michigan Health System, 1500 East Medical Center Drive, 2130 Taubman Center, SPC 5340, Ann Arbor, MI 48109-5340, USA.
Abstract:
Natural language processing systems (NLPs) and large language models (LLMs) have the potential to revolutionize hand surgery by streamlining workflows, enhancing patient-care, and advancing research capabilities. NLPs are particularly adept at processing unstructured clinical data, enabling more efficient research, quality improvement initiatives, and patient safety monitoring. LLMs contribute through patient education, real-time clinical decision support, and reducing administrative burdens with automated documentation. However, challenges must be resolved to fully realize their benefits. Overcoming these barriers could pave the way for transformative advancements in hand surgery and health care.
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