60 citations · 262 across the 28 of their papers we have counts for
6 papers · 1 filter
How Well Can Modern LLMs Act as Agent Cores in Radiology Environments?
Qiaoyu Zheng, Chaoyi Wu, Weike Zhao +5
Radiology, with its heterogeneous modalities, anatomies, and evolving protocols, is a natural yet high-stakes testbed for agentic AI. As LLMs grow more capable and tool ecosystems…
Towards Evaluating and Building Versatile Large Language Models for Medicine
Chaoyi Wu, Pengcheng Qiu, Jinxin Liu +5
In this study, we present MedS-Bench, a comprehensive benchmark designed to evaluate the performance of large language models (LLMs) in clinical contexts. Unlike existing benchmark…
AutoRG-Brain: Grounded Report Generation for Brain MRI
Jiayu Lei, Xiaoman Zhang, Chaoyi Wu +6
Radiologists are tasked with interpreting a large number of images in a daily base, with the responsibility of generating corresponding reports. This demanding workload elevates th…
RadGenome-Chest CT: A Grounded Vision-Language Dataset for Chest CT Analysis
Xiaoman Zhang, Chaoyi Wu, Ziheng Zhao +4
Developing generalist foundation model has recently attracted tremendous attention among researchers in the field of AI for Medicine (AI4Medicine). A pivotal insight in developing…
Knowledge-enhanced Visual-Language Pretraining for Computational Pathology
Xiao Zhou, Xiaoman Zhang, Chaoyi Wu +3
In this paper, we consider the problem of visual representation learning for computational pathology, by exploiting large-scale image-text pairs gathered from public resources, alo…
Towards Building Multilingual Language Model for Medicine
Pengcheng Qiu, Chaoyi Wu, Xiaoman Zhang +5
The development of open-source, multilingual medical language models can benefit a wide, linguistically diverse audience from different regions. To promote this domain, we present…