Using LLMs to Simplify Real-World Evidence Research - In Person at ISPOR 2025
- kenashman
- Jun 12
- 1 min read
Event 13 May 2025 ISPOR
Discover how artificial intelligence (AI) is transforming real-world evidence (RWE) research, enabling more efficient data extraction, analysis, and validation from complex medical records.
This course provides a structured, four-hour deep dive into the applications, challenges, and opportunities of AI in healthcare data science.
Technical Topics Include:
AI applications in medical records: Addressing foundational challenges in data extraction and analysis
Practical use cases: AI-driven insights from longitudinal medical records
System considerations: Navigating data access, patient privacy, and regulatory compliance
Technical challenges: Complexities of deploying AI in healthcare settings
Safety and validation systems: Ensuring accuracy, reliability, and regulatory alignment in AI-driven RWE research
Emerging opportunities: AI-driven advancements that enhance patient care and support regulatory decision-making
This Course Includes Tools and Concepts That Can Be Immediately Applied, Including:
Practical demonstrations of AI-driven RWE applications
Frameworks for managing privacy and security when using AI in healthcare data
Strategies for integrating AI tools into real-world evidence workflows
Best practices for validating AI-driven insights in regulatory and clinical settings
This course is designed for professionals in RWE research, healthcare analytics, and regulatory decision-making who want to leverage AI to improve data-driven insights and patient outcomes.
