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Generative Artificial Intelligence and Prompt Engineering: A Primer for Orthopaedic Surgeons.

Amber N Carroll¹, Lewis A Storms¹, Chaitu Malempati²

¹College of Medicine, University of Kentucky, Lexington, Kentucky.

|October 3, 2024

Summary

Generative artificial intelligence (AI) offers transformative potential in orthopedic care by improving diagnostics and patient management. Effective prompt engineering is key for orthopaedic surgeons to harness AI

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Area of Science:

Orthopedic Surgery
Artificial Intelligence
Medical Informatics

Background:

Generative artificial intelligence (AI) is rapidly evolving, presenting new opportunities in healthcare.
Traditional AI differs from generative AI in its capacity to create novel information.
Generative AI can assist orthopaedic surgeons with tasks like literature reviews and patient interaction.

Purpose of the Study:

To explore the potential of generative AI in revolutionizing orthopedic care.
To highlight the importance of prompt engineering for effective use of large language models (LLMs) in clinical settings.
To inform orthopaedic surgeons about different prompt types and LLM limitations.

Main Methods:

Discussion of generative AI capabilities in orthopedics.
Explanation of prompt engineering principles for LLMs.
Categorization of prompt types (open-ended, focused, choice-based) for clinical tasks.
Identification of LLM limitations (token limits, context windows, hallucinations) and ethical considerations.

Main Results:

Generative AI can enhance diagnostic accuracy, treatment planning, and patient management through data-driven insights.
Prompt engineering enables tailored AI responses for specific clinical tasks, improving precision and utility.
Understanding LLM limitations and ethical concerns is vital for responsible AI implementation.

Conclusions:

Generative AI holds significant promise for advancing orthopedic care.
Strategic use of prompt engineering and awareness of LLM limitations are crucial for maximizing AI benefits.
Ethical considerations must guide the integration of AI in clinical practice.