2 citations · 3 across the 5 of their papers we have counts for
5 papers
A unified multi-task framework enables interpretable chest radiograph analysis
Lijian Xu, Ziyu Ni, Xinglong Liu +3
While multimodal deep learning has advanced medical imaging analysis, existing black-box systems \textcolor{black}{may remain confined to isolated tasks, often overlooking} the tru…
A foundation model for generalizable disease diagnosis in chest X-ray images
Lijian Xu, Ziyu Ni, Hao Sun +2
Medical artificial intelligence (AI) is revolutionizing the interpretation of chest X-ray (CXR) images by providing robust tools for disease diagnosis. However, the effectiveness o…
MedViLaM: A multimodal large language model with advanced generalizability and explainability for medical data understanding and generation
Lijian Xu, Hao Sun, Ziyu Ni +2
Medicine is inherently multimodal and multitask, with diverse data modalities spanning text, imaging. However, most models in medical field are unimodal single tasks and lack good…
Learning A Multi-Task Transformer Via Unified And Customized Instruction Tuning For Chest Radiograph Interpretation
Lijian Xu, Ziyu Ni, Xinglong Liu +3
The emergence of multi-modal deep learning models has made significant impacts on clinical applications in the last decade. However, the majority of models are limited to single-ta…
Voxel2Hemodynamics: An End-to-end Deep Learning Method for Predicting Coronary Artery Hemodynamics
Ziyu Ni, Linda Wei, Lijian Xu +4
Local hemodynamic forces play an important role in determining the functional significance of coronary arterial stenosis and understanding the mechanism of coronary disease progres…