November 17: AI-Powered HEOR: Advancing Insights and Decisions with Large Language Models - In Person at ISPOR Europe 2024
![event-Short-Courses event-Short-Courses](https://www.ispor.org/images/default-source/default-album/event-short-courses.png?sfvrsn=934c5e55_6)
November 17, 2024
AI-Powered HEOR: Advancing Insights and Decisions with Large Language Models (in person)
LEVEL: Intermediate
TRACK: Study Approaches
LENGTH: 4 Hours | Course runs 1 day
This short course is offered in-person at the ISPOR Europe 2024 conference. Separate registration is required. Visit the ISPOR Europe 2024 Program page to register and learn more.
Sunday, 17 November 2024 | Course runs 1 Day
13:00-17:00 Central European Time (CET)
DESCRIPTION
Separate registration required.
This course delves into the transformative role of Generative AI, particularly large language models (LLMs), in enhancing key areas of HEOR such as systematic literature reviews (SLR) and real-world evidence synthesis, economic modeling, regulatory decision-making, and the development of external control arms.
Participants will learn to apply Generative AI technologies to conduct comprehensive and efficient systematic literature reviews, synthesize evidence at scale, and construct robust economic models that support healthcare policy and market strategies. The course also covers the strategic use of AI in developing external control arms, essential for clinical trials and regulatory submissions, thereby improving the quality and speed of healthcare decisions.
This program is ideal for HEOR data analysts, outcome researchers, epidemiologist, health economists, regulatory affairs professionals, and anyone in all substance matter fields involved in the planning and implementation of healthcare strategies. Through a combination of expert lectures, hands-on exercises, and case study analyses, attendees will gain practical skills and insights into leveraging AI to streamline research processes, enhance data analysis, and forge ahead in the dynamic field of healthcare research and policy. Participants are required to bring a laptop with the capability to connect to Wi-Fi and sufficient processing power to handle basic analytical tasks. Access to an LMS for course materials, discussion boards, and any required pre-course or post-course work. For conducting SLR, participants may need access to databases such as PubMed, Cochrane Library, or Embase.
PREREQUISITE: Students are expected to have a basic knowledge of HEOR concepts, health data analysis, research methods, and interest in artificial intelligence.
Registrants receive a digital course book. Copyright, Trademark and Confidentiality Policies apply.
FACULTY MEMBERS
Xiaoyan Wang, PhD
Professor
Tulane University
New Orleans, LA, USA
Jagpreet Chhatwal, PhD
Associate Professor
Harvard Medical School
Boston, MA, USA
Hua Xu, PhD
Robert T. McCluskey Professor of Biomedical Informatics and Data Science, Vice Chair for Research and Development, Department of Biomedical Informatics and Data Science, and Assistant Dean for Biomedical Informatics, Yale School of Medicine
New Haven, CT, USA
Turgay Ayer, PhD
Professor
H. Milton Stewart School of Industrial and Systems Engineering,
Georgia Institute of Technology
Atlanta, GA, USA
Basic Schedule:
4 Hours | Course runs 1 Day