4 citations · 7 across the 4 of their papers we have counts for
4 papers
Aligning Large Language Models with Healthcare Stakeholders: A Pathway to Trustworthy AI Integration
Kexin Ding, Mu Zhou, Akshay Chaudhari +2
The wide exploration of large language models (LLMs) raises the awareness of alignment between healthcare stakeholder preferences and model outputs. This alignment becomes a crucia…
Eyes Tell the Truth: GazeVal Highlights Shortcomings of Generative AI in Medical Imaging
David Wong, Bin Wang, Gorkem Durak +23
The demand for high-quality synthetic data for model training and augmentation has never been greater in medical imaging. However, current evaluations predominantly rely on computa…
Almanac Copilot: Towards Autonomous Electronic Health Record Navigation
Cyril Zakka, Joseph Cho, Gracia Fahed +9
Clinicians spend large amounts of time on clinical documentation, and inefficiencies impact quality of care and increase clinician burnout. Despite the promise of electronic medica…
A Generalist Model for Diverse Text-Guided Medical Image Synthesis
Joseph Cho, Mrudang Mathur, Cyril Zakka +15
Deep learning algorithms require extensive data to achieve robust performance. However, data availability is often restricted in the medical domain due to patient privacy concerns.…