Natural Language Processing and Large Language Models

Area of Science:

• Medical Informatics
• Artificial Intelligence in Medicine
• Surgical Innovation

Background:

• Natural language processing systems (NLPs) and large language models (LLMs) offer significant potential for advancing hand surgery.
• These AI technologies can streamline clinical workflows, improve patient care, and enhance research capabilities within the specialty.

Purpose of the Study:

• To explore the potential applications of NLPs and LLMs in hand surgery.
• To identify the benefits and challenges associated with implementing these technologies in clinical practice and research.

Main Methods:

• Review of current literature on NLP and LLM applications in healthcare.
• Analysis of the specific capabilities of NLPs in processing unstructured clinical data.
• Evaluation of LLM contributions to patient education, clinical decision support, and administrative task automation.

Main Results:

• NLPs can enhance research efficiency, quality improvement, and patient safety by analyzing unstructured clinical data.
• LLMs can improve patient education, provide real-time clinical decision support, and reduce administrative burdens through automated documentation.
• Key challenges remain in fully realizing the benefits of these technologies in hand surgery.

Conclusions:

• NLPs and LLMs hold transformative potential for hand surgery, impacting workflows, patient care, and research.
• Overcoming implementation challenges is crucial for leveraging these AI advancements.
• Successful integration promises significant progress in hand surgery and overall healthcare.