10 citations · 19 across the 4 of their papers we have counts for
4 papers
ELEVATE-GenAI: Reporting Guidelines for the Use of Large Language Models in Health Economics and Outcomes Research: an ISPOR Working Group on Generative AI Report
Rachael L. Fleurence, Dalia Dawoud, Jiang Bian +5
Introduction: Generative artificial intelligence (AI), particularly large language models (LLMs), holds significant promise for Health Economics and Outcomes Research (HEOR). Howev…
Generative AI in Health Economics and Outcomes Research: A Taxonomy of Key Definitions and Emerging Applications, an ISPOR Working Group Report
Rachael Fleurence, Xiaoyan Wang, Jiang Bian +5
Objective: This article offers a taxonomy of generative artificial intelligence (AI) for health economics and outcomes research (HEOR), explores its emerging applications, and outl…
Environment Scan of Generative AI Infrastructure for Clinical and Translational Science
Betina Idnay, Zihan Xu, William G. Adams +54
This study reports a comprehensive environmental scan of the generative AI (GenAI) infrastructure in the national network for clinical and translational science across 36 instituti…
Generative AI for Health Technology Assessment: Opportunities, Challenges, and Policy Considerations
Rachael Fleurence, Jiang Bian, Xiaoyan Wang +4
This review introduces the transformative potential of generative Artificial Intelligence (AI) and foundation models, including large language models (LLMs), for health technology…