Accurate hemodynamic assessment is of significant clinical value in the diagnosis, prognosis, and treatment planning of cardiovascular and cerebrovascular diseases. However, obtaining noninvasive, rapid, and high-fidelity hemodynamic information remains challenging. Invasive measurements carry risks, numerical simulati...
Zhuo Li, Yao Zeng, Meng-Fei Wang et al.· IEEE journal of biomedical a...· 0 citations
To evaluate whether large language model assistance improves radiologists’ agreement with a text-based reference standard in inferring the modified American Heart Association carotid plaque classification from free-text MRI reports, and whether a lightweight model can perform well under criteria-guided prompting. This...
Meng-Fei Wang, Yi-Xiao Tang, Yu-Lu Yang et al.· Insights into Imaging· 0 citations
RATIONALE AND OBJECTIVES
To propose a new imaging biomarker, the pulmonary artery-to-vein volume difference (PAVVD), and evaluate its efficacy in risk stratification of acute pulmonary embolism (APE) compared with traditional computed tomography pulmonary angiography (CTPA) parameters, as well as the impact of chronic...
Xin-Yu Song, Li-Fang Ye, Bi-Cong Yan et al.· Academic Radiology· 0 citations
A foundation model for non-contrast computed tomography, a multi-task AI system built on a self-supervised foundation model that detects 11 acute abdominal conditions and performs three risk-stratification subtasks from NCCT images is presented.
Chao Zhu, Rui-Peng Zhang, Xin-Yu Song et al.· Nature Communications· 0 citations
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