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Frontiers in Neuroscience|January 28, 2021
Deep Network for the Automatic Segmentation and Quantification of Intracranial Hemorrhage on CTJun Xu, Rongguo Zhang, Zijian Zhou, et al.
Chinese Medical Journal|October 12, 2023
A machine learning model for diagnosing acute pulmonary embolism and comparison with Wells score, revised Geneva score, and Years algorithmLinfeng Xi, Han Kang, Mei Deng, et al.
Quantitative Imaging in Medicine and Surgery|January 15, 2024
Clot ratio, new clot burden score with deep learning, correlates with the risk stratification of patients with acute pulmonary embolismLinfeng Xi, Feiya Xu, Han Kang, et al.
Korean Journal of Radiology|June 12, 2020
Automatic Detection and Classification of Rib Fractures on Thoracic CT Using Convolutional Neural Network: Accuracy and FeasibilityQing Qing Zhou, Jiashuo Wang, Wen Tang, et al.
BMC Pulmonary Medicine|March 15, 2025
Evaluation of respiratory muscle dysfunction in patients with idiopathic pulmonary fibrosis: a prospective observational study with magnetic resonance imagingXiaoyan Yang, Hongyi Wang, Anqi Liu, et al.
European Radiology|November 17, 2020
Automatic detection and classification of rib fractures based on patients' CT images and clinical information via convolutional neural networkQing-Qing Zhou, Wen Tang, Jiashuo Wang, et al.
Clinical Imaging|October 1, 2021
Precise anatomical localization and classification of rib fractures on CT using a convolutional neural networkQing-Qing Zhou, Zhang-Chun Hu, Wen Tang, et al.
Radiology. Artificial Intelligence|May 3, 2021
Evaluating a Fully Automated Pulmonary Nodule Detection Approach and Its Impact on Radiologist PerformanceKai Liu, Qiong Li, Jiechao Ma, et al.
Quantitative Imaging in Medicine and Surgery|October 23, 2023
Coronary computed tomography angiography analysis using artificial intelligence for stenosis quantification and stent segmentation: a multicenter studyQingtao Meng, Pengxin Yu, Siyuan Yin, et al.
Annals of Translational Medicine|May 2, 2020
Development of a deep learning model for classifying thymoma as Masaoka-Koga stage I or II via preoperative CT imagesLei Yang, Wenjia Cai, Xiaoyu Yang, et al.
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