Your First Healthcare AI Assistant: Hands-On Prompting #

Learning Objectives #

• Practice prompt engineering for healthcare applications
• Build a functional healthcare Q&A system
• Understand the importance of prompt validation and testing
• Learn to implement safety guardrails

Prompt Engineering for Healthcare #

• The anatomy of a good prompt
• Techniques: few-shot learning, chain-of-thought, role-playing
• Healthcare-specific considerations: requesting sources, acknowledging uncertainty
• Examples of effective prompts for different tasks

Building the Healthcare Q&A Assistant #

• Using HuggingFace LLM with system and user prompts
• Test assistant with various types of questions and refine prompts based on results
• Extend the assistant to handle a specific medical domain of choice (e.g., diabetes management, mental health basics)
• Base code will be provided in Jupyter notebook or Google Colab

Key Features to Implement #

• Input validation (filtering inappropriate medical questions)
• Disclaimer generation (“This is not medical advice…”)

Testing and Validation #

• Creating test cases for medical Q&A
• Measuring usefulness vs. safety trade-offs
• User testing with non-medical students
• Iterative improvement based on feedback

Safety Guardrails #

• Implementing content filters
• Recognizing when to refuse to answer
• Proper medical disclaimers
• Escalation protocols