5 papers
Learning Directional Semantic Transitions for Longitudinal Chest X-ray Analysis
Zhangfeng Hu, Zefan Yang, Ge Wang +4
Chest X-ray (CXR) interpretation often requires longitudinal comparison to assess disease progression. Existing approaches typically rely on temporal feature fusion or inter-study…
Reflections from Research Roundtables at the Conference on Health, Inference, and Learning (CHIL) 2025
Emily Alsentzer, Marie-Laure Charpignon, Bill Chen +90
The 6th Annual Conference on Health, Inference, and Learning (CHIL 2025), hosted by the Association for Health Learning and Inference (AHLI), was held in person on June 25-27, 2025…
Phrase-grounded Fact-checking for Automatically Generated Chest X-ray Reports
Razi Mahmood, Diego Machado-Reyes, Joy Wu +7
With the emergence of large-scale vision language models (VLM), it is now possible to produce realistic-looking radiology reports for chest X-ray images. However, their clinical tr…
Granite Vision: a lightweight, open-source multimodal model for enterprise Intelligence
Granite Vision Team, Leonid Karlinsky, Assaf Arbelle +60
We introduce Granite Vision, a lightweight large language model with vision capabilities, specifically designed to excel in enterprise use cases, particularly in visual document un…
Anatomically-Grounded Fact Checking of Automated Chest X-ray Reports
R. Mahmood, K. C. L. Wong, D. M. Reyes +8
With the emergence of large-scale vision-language models, realistic radiology reports may be generated using only medical images as input guided by simple prompts. However, their p…