Hasika Oggi
University of California Berkeley, United States
Publications
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Review Article
Large Language Models for Patient Education for Atrial Fibrillation
Author(s): Gloria Wu*, Hrishi Paliath-Pathiyal, Obaid Khan, Margaret Wang, Swara Tewari, Hasika Oggi, Riki Toram, Paul J. Wang and David Lee
Atrial fibrillation (AF) is the most common arrhythmia globally, affecting over 37 million individuals. AF substantially increases the risk of stroke, heart failure, and mortality. With the advent of the internet, most patients use Large Language Models (LLMs) for health education. In terms of monthly users, ChatGPT has 800M, Gemini has 350M, Claude.ai has 18.9M, Meta has 350M, and Grok has 64M. These LLMs use different training models. The purpose of this small study was to evaluate large language models (LLMs) for atrial fibrillation patient education... Read More»

