24 citations · 29 across the 9 of their papers we have counts for
9 papers
A Chain of Diagnosis Framework for Accurate and Explainable Radiology Report Generation
Haibo Jin, Haoxuan Che, Sunan He +1
Despite the progress of radiology report generation (RRG), existing works face two challenges: 1) The performances in clinical efficacy are unsatisfactory, especially for lesion at…
Large-scale Self-supervised Video Foundation Model for Intelligent Surgery
Shu Yang, Fengtao Zhou, Leon Mayer +16
Computer-Assisted Intervention (CAI) has the potential to revolutionize modern surgery, with surgical scene understanding serving as a critical component in supporting decision-mak…
MedBookVQA: A Systematic and Comprehensive Medical Benchmark Derived from Open-Access Book
Sau Lai Yip, Sunan He, Yuxiang Nie +4
The accelerating development of general medical artificial intelligence (GMAI), powered by multimodal large language models (MLLMs), offers transformative potential for addressing…
EvdCLIP: Improving Vision-Language Retrieval with Entity Visual Descriptions from Large Language Models
GuangHao Meng, Sunan He, Jinpeng Wang +7
Vision-language retrieval (VLR) has attracted significant attention in both academia and industry, which involves using text (or images) as queries to retrieve corresponding images…
UniBiomed: A Universal Foundation Model for Grounded Biomedical Image Interpretation
Linshan Wu, Yuxiang Nie, Sunan He +12
The integration of AI-assisted biomedical image analysis into clinical practice demands AI-generated findings that are not only accurate but also interpretable to clinicians. Howev…
FreeTumor: Large-Scale Generative Tumor Synthesis in Computed Tomography Images for Improving Tumor Recognition
Linshan Wu, Jiaxin Zhuang, Yanning Zhou +12
Tumor is a leading cause of death worldwide, with an estimated 10 million deaths attributed to tumor-related diseases every year. AI-driven tumor recognition unlocks new possibilit…
An Explainable Biomedical Foundation Model via Large-Scale Concept-Enhanced Vision-Language Pre-training
Yuxiang Nie, Sunan He, Yequan Bie +14
The clinical adoption of artificial intelligence (AI) in medical imaging requires models that are both diagnostically accurate and interpretable to clinicians. While current multim…
GSCo: Towards Generalizable AI in Medicine via Generalist-Specialist Collaboration
Sunan He, Yuxiang Nie, Hongmei Wang +21
Generalist foundation models (GFMs) are renowned for their exceptional capability and flexibility in effectively generalizing across diverse tasks and modalities. In the field of m…
MegaScale: Scaling Large Language Model Training to More Than 10,000 GPUs
Ziheng Jiang, Haibin Lin, Yinmin Zhong +29
We present the design, implementation and engineering experience in building and deploying MegaScale, a production system for training large language models (LLMs) at the scale of…