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Apply generative AI and LLMs in HEOR research

This course introduces generative artificial intelligence (Gen AI), with a focus on large language models (LLMs), and their transformative applications in health economics and outcomes research (HEOR). It explores practical use cases, access methods beyond chatbots, and considerations for responsible use.

Technical topics include:

• Fundamentals of generative AI and LLMs
• Methods for accessing and using LLMs beyond chat-based tools
• Prompt engineering for scientific research
• Privacy and security considerations in HEOR applications

This course includes tools and concepts that can be immediately applied, including:

• Applications in systematic literature reviews (SLRs), real-world evidence analysis, and economic evaluation
• Hands-on prompt engineering techniques for research tasks
• Practical exercises using Python and AI frameworks
• Approaches for integrating Gen AI into HEOR workflows

Participants will gain the knowledge and skills to begin using generative AI techniques to enhance HEOR research and support more efficient, data-driven decision-making. Practical exercises using Python and relevant AI frameworks will be incorporated for participants to follow along.

PREREQUISITES: Students should have a general understanding of common HEOR concepts such as SLRs and cost-effectiveness models. Knowledge of Python or similar programming languages such as R is considered a benefit but not required.

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*Conference attendance is not required to attend an ISPOR Short Course. Separate registration is required for conference attendees.

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