| See the forest for the trees: Joint spatial and temporal recurrent neural networks for video-based person re-identification Z Zhou, Y Huang, W Wang, L Wang, T Tan Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 386 | 2017 |
| A deep learning approach to characterize 2019 coronavirus disease (COVID-19) pneumonia in chest CT images Q Ni, ZY Sun, L Qi, W Chen, Y Yang, L Wang, X Zhang, L Yang, Y Fang, ... European radiology 30, 6517-6527, 2020 | 228 | 2020 |
| Joint learning for pulmonary nodule segmentation, attributes and malignancy prediction B Wu, Z Zhou, J Wang, Y Wang 2018 IEEE 15th international symposium on biomedical imaging (ISBI 2018 …, 2018 | 153 | 2018 |
| Lower circulating interferon-gamma is a risk factor for lung fibrosis in COVID-19 patients ZJ Hu, J Xu, JM Yin, L Li, W Hou, LL Zhang, Z Zhou, YZ Yu, HJ Li, ... Frontiers in immunology 11, 585647, 2020 | 135 | 2020 |
| Multicenter cohort study demonstrates more consolidation in upper lungs on initial CT increases the risk of adverse clinical outcome in COVID-19 patients Q Yu, Y Wang, S Huang, S Liu, Z Zhou, S Zhang, Z Zhao, Y Yu, Y Yang, ... Theranostics 10 (12), 5641, 2020 | 109 | 2020 |
| Long-term follow-up of persistent pulmonary pure ground-glass nodules with deep learning–assisted nodule segmentation LL Qi, BT Wu, W Tang, LN Zhou, Y Huang, SJ Zhao, L Liu, M Li, L Zhang, ... European radiology 30, 744-755, 2020 | 85 | 2020 |
| Dynamic evolution of COVID-19 on chest computed tomography: experience from Jiangsu Province of China YC Wang, H Luo, S Liu, S Huang, Z Zhou, Q Yu, S Zhang, Z Zhao, Y Yu, ... European Radiology 30, 6194-6203, 2020 | 58 | 2020 |
| Cascaded generative and discriminative learning for microcalcification detection in breast mammograms F Zhang, L Luo, X Sun, Z Zhou, X Li, Y Yu, Y Wang Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 48 | 2019 |
| Diagnose like a radiologist: Hybrid neuro-probabilistic reasoning for attribute-based medical image diagnosis G Zhao, Q Feng, C Chen, Z Zhou, Y Yu IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (11), 7400 …, 2021 | 34 | 2021 |
| AI-based analysis of CT images for rapid triage of COVID-19 patients Q Xu, X Zhan, Z Zhou, Y Li, P Xie, S Zhang, X Li, Y Yu, C Zhou, L Zhang, ... NPJ digital medicine 4 (1), 75, 2021 | 32 | 2021 |
| Natural history of pathologically confirmed pulmonary subsolid nodules with deep learning–assisted nodule segmentation LL Qi, JW Wang, L Yang, Y Huang, SJ Zhao, W Tang, YJ Jin, ZW Zhang, ... European Radiology 31, 3884-3897, 2021 | 29 | 2021 |
| From unilateral to bilateral learning: Detecting mammogram masses with contrasted bilateral network Y Liu, Z Zhou, S Zhang, L Luo, Q Zhang, F Zhang, X Li, Y Wang, Y Yu Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019 | 28 | 2019 |
| Community detection based on an improved modularity Z Zhou, W Wang, L Wang Pattern Recognition: Chinese Conference, CCPR 2012, Beijing, China …, 2012 | 25 | 2012 |
| Exploring generalized shape analysis by topological representations Z Zhou, Y Huang, L Wang, T Tan Pattern Recognition Letters 87, 177-185, 2017 | 24 | 2017 |
| Performance of Deep-learning-based Artificial Intelligence on Detection of Pulmonary Nodules in Chest CT. LI Xinling, GUO Fangfang, Z Zhen, F Zhang, W Qin, P Zhijun, SU Datong, ... Chinese journal of lung cancer 22 (6), 2019 | 23 | 2019 |
| A deep-learning model for intracranial aneurysm detection on CT angiography images in China: a stepwise, multicentre, early-stage clinical validation study B Hu, Z Shi, L Lu, Z Miao, H Wang, Z Zhou, F Zhang, R Wang, X Luo, F Xu, ... The Lancet Digital Health 6 (4), e261-e271, 2024 | 20 | 2024 |
| Development and validation of a clinically applicable deep learning strategy (HONORS) for pulmonary nodule classification at CT: a retrospective multicentre study W Lv, Y Wang, C Zhou, M Yuan, M Pang, X Fang, Q Zhang, C Huang, X Li, ... Lung Cancer 155, 78-86, 2021 | 20 | 2021 |
| The application of artificial intelligence to chest medical image analysis F Liu, J Tang, J Ma, C Wang, Q Ha, Y Yu, Z Zhou Intelligent Medicine 1 (3), 104-117, 2021 | 12 | 2021 |
| Predicting invasiveness of lung adenocarcinoma at chest CT with deep learning ternary classification models Z Pan, G Hu, Z Zhu, W Tan, W Han, Z Zhou, W Song, Y Yu, L Song, Z Jin Radiology 311 (1), e232057, 2024 | 10 | 2024 |
| Proposing a deep learning-based method for improving the diagnostic certainty of pulmonary nodules in CT scan of chest YW Wang, JW Wang, SX Yang, LL Qi, HL Lin, Z Zhou, YZ Yu European Radiology 31 (11), 8160-8167, 2021 | 10 | 2021 |
