Artificial Intelligence in Orthopaedics

Courtesy: Prof Mohamed Imam, Surrey, UK

Introduction to Generative AI in Orthopaedics

• Generative AI (e.g., ChatGPT, Gemini) differs from traditional AI by creating new content (text, images).
• Applications: Diagnostics, treatment planning, patient communication, and workflow automation.
• Enhance precision, personalize care, and improve efficiency.

Large Language Models (LLMs) in Healthcare

What are LLMs?

• Models like GPT-4, Claude, and Gemini trained on vast datasets to generate human-like text.

Orthopaedic Uses:

• Literature reviews, patient education, clinical note generation.

Key Parameters:

• Tokens: Units of text processed (words/sub words).
• Context Window: Memory span for continuity (e.g., 32k tokens in GPT-4).

Prompt Engineering Basics

• Definition: Crafting inputs to guide AI outputs.
• The quality and specificity of the response generally improve with the inclusion of more detailed elements

Components of a Good Prompt:

• Persona (role), Task (action),
• Context (details), Format (structure).

Example:

• “Act as an orthopaedic surgeon. Summarize post-op care for ACL reconstruction in bullet points.”

Persona – Defines the role the LLM adopts.

Task – Specifies the action to perform.

Context – Provides relevant background information.

Format – Indicates the desired output style or structure

Types of Prompts

• Open-Ended: Broad, creative prompts allowing wide-ranging responses – brainstorming (e.g.,“Develop discharge instructions for Total Knee Replacement.””).
• Focused: Specific queries (e.g., “What are the specific postoperative care guidelines for patients undergoing knee replacement surgery and going to a skilled nursing facility”).
• Chained: Multi-step reasoning (e.g., ““Develop an outline for a curriculum for second-year Orthopaedic Surgery residents, then follow this prompt with another to expand on the pediatric Orthopaedics rotation”).
• Choice-Based: Decision support (e.g., “Compare outcomes of cemented vs. uncemented hip implants”).
• Exploratory: Prompts for analysing data or generating new insights, useful in research (eg. “Analyse the provided systematic review paper and suggest 3 future research ideas.”)

 

• Artificial Intelligence (AI) encompasses all technologies that enable machines to mimic human intelligence.
• Within AI, Machine Learning (ML) refers to systems that learn from data to improve their performance.
• A subset of ML is Generative AI (Gen AI), which focuses on producing new content (text, images, etc.) rather than just analyzing data.
• Large Language Models (LLMs), such as GPT4, are a specific type of generative AI designed to understand and produce human-like language.
• Thus, LLMs are nested within Gen AI, which is nested within ML, and all fall under the larger category of AI.

Advanced Prompting Techniques

Best Practices:

• Use delimiters (e.g., quotes, brackets) for clarity.
• Provide examples to guide output style.
• Split complex tasks into steps.
• Table: Advanced methods (e.g., “Meta-language creation” for medical shorthand).

Limitations and Ethical Concerns

• Hallucinations: AI-generated inaccuracies (mitigated by cross-verification).
• Bias: Training data may reflect historical inequities.
• Privacy
• Accountability: AI aids but doesn’t replace clinical judgment.

X-ray Interpretation – Left Elbow (AP & Lateral Views)

• Patient: Lakshmi (Female)
• Date: 04-May-2025
• View: AP and Lateral views of the left elbow

Impression:

• No radiological evidence of fracture or dislocation in the left elbow.
• Findings are within normal limits.
• Case Study / Application

 

Example:

• Using ChatGPT to draft patient discharge instructions for total knee arthroplasty.
• Before/After: Compare generic vs. engineered prompts for accuracy.

Future Directions

• Fine-Tuning LLMs: Adapt models to orthopaedic datasets.
• Continuous Learning: Feedback loops to improve accuracy.
• Research Needs: Studies on AI’s impact on surgical outcomes.
• Conclusion & Call to Action

Summary:

• Generative AI can transform orthopaedics but requires prompt engineering skills and ethical vigilance.

Action

• Surgeons should engage with AI tools, attend workshops, and contribute to AI training