Large Language Models in Orthopaedics: Definitions, Uses, and Limitations.

Area of Science:

• Artificial Intelligence and Machine Learning
• Medical Informatics
• Orthopaedic Surgery

Background:

• Large language models (LLMs) are advanced artificial intelligence (AI) systems adept at natural language processing and generation.
• These AI tools present numerous opportunities within the medical field, particularly in specialized areas like orthopaedics.

Purpose of the Study:

• To explore the potential applications of LLMs in orthopaedics, encompassing clinical practice, research endeavors, and educational contexts.
• To highlight the critical need for patient safety and high standards in the development and deployment of LLM-based orthopaedic tools.
• To address the existing methodological, ethical, and regulatory challenges associated with LLM utilization in healthcare.

Main Methods:

• Review of current literature and expert opinion on large language models in artificial intelligence.
• Analysis of potential use cases and associated risks within the orthopaedic specialty.
• Discussion of ethical considerations, regulatory frameworks, and patient-centric priorities.

Main Results:

• LLMs demonstrate substantial promise for revolutionizing text processing and generation tasks in orthopaedics.
• Significant challenges related to data privacy, algorithmic bias, and clinical validation require careful navigation.
• The integration of LLMs necessitates a proactive approach to ensure patient safety and ethical compliance.

Conclusions:

• Orthopaedic surgeons must be informed about the capabilities and limitations of LLMs.
• Advocacy for LLM development that prioritizes patient and caregiver needs is essential.
• A balanced approach is required to harness the benefits of LLMs while mitigating potential risks in orthopaedic care.