September 4, 2024 - September 5, 2024
Advance your AI and machine learning proficiency — #3 on the list of ISPOR 2024-2025 Top 10 HEOR Trends Report!
Explore large language models (LLMs) like GPT, BERT, and LLaMA, and how to use them for real world evidence generation and HEOR.
Topics include:
- Basics of large language models,
- training models,
- using the models for health data analysis,
- optimal model selection for specific tasks, and
- ethical considerations related to LLMs and health data.
Participants will be introduced to prompt engineering using practical examples, allowing students to apply it to real LLMs, including:
- Examining medical data summarization using LLMs,
- evidence generation,
- analysis of healthcare data, and
- the automation of value dossier creation.
By completing this comprehensive course, participants will have the knowledge and skills to responsibly employ LLMs for practical tasks in RWE and HEOR while addressing regulatory requirements.
To participate in hands-on activities, participants must have access to a laptop and a ChatGPT personal or corporate account.
PREREQUISITE: General knowledge of ChatGPT is important.
LEVEL: Intermediate
TRACK: Real World Data & Information Systems
HEOR Key Competency: 5.3 Health Economic Modeling
Faculty
Schedule:
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.