Event

Gain hands-on experience with large language models for HEOR and real-world evidence

Explore large language models (LLMs) like GPT, BERT, and LLaMA, and learn how to use them for real-world evidence generation and HEOR. This course covers the basics of large language models, training methods, using models for health data analysis, optimal model selection for specific tasks, and ethical considerations related to LLMs and health data.

Technical topics include:

• Introduction to large language models (LLMs) such as GPT, BERT, and LLaMA.

• Training LLMs and using them for health data analysis.

• Optimal model selection for specific HEOR and RWE tasks.

• Ethical considerations and regulatory requirements for LLMs in healthcare.

This course includes hands-on learning and tools that can be immediately applied, including:

• Practical examples of prompt engineering for real LLMs.

• Exercises in medical data summarization and evidence generation.

• Techniques for automating healthcare data analysis and value dossier creation.

• Real-world applications of LLMs in RWE and HEOR tasks.

Participants will gain the knowledge and skills to responsibly employ LLMs for practical applications while addressing ethical and regulatory considerations. To participate in hands-on activities, participants must have access to a laptop and a ChatGPT personal or corporate account.

LEVEL: Intermediate 
TRACK: Real-World Data & Information Systems

LENGTH: 4 Hours | Course runs 2 consecutive days, 2 hours each day

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ISPOR short courses are designed to enhance knowledge and techniques in core health economics and outcomes research (HEOR) topics as well as emerging trends in the field. Short courses offer 4 or 8 hours of premium scientific education and an electronic course book. Active attendee participation combined with our expert faculty creates an immersive and impactful learning experience. Short courses are not recorded and are only available during the live course presentation.