Multicenter Acute Ischemic Stroke, MRI and Clinical Text Dataset

Principal Investigator(s):  View help for Principal Investigator(s) Zhiqiang Zhang, National Key Laboratory for Novel Software Technology, Department of Computer Science and Technology, Nanjing University. 2. Department of Diagnostic Radiology, Afliated jinling, Hospital, Medical School of Nanjing University; Chuanzhen Xu, National Key Laboratory for Novel Software Technology, Department of Computer Science and Technology, Nanjing University. 2. Department of Diagnostic Radiology, Afliated jinling, Hospital, Medical School of Nanjing University. 3. State Key Laboratory of Analytical Chemistry for Life Science, Nanjing University; Yi Zhou , Department of Radiology, Jinling Hospital, Nanjing University School of Medicine; Xin Deng , National Key Laboratory for Novel Software Technology, Department of Computer Science and Technology, Nanjing University; Yuying Liu, National Key Laboratory for Novel Software Technology, Department of Computer Science and Technology, Nanjing University; Xiaoqing Cheng, Department of Radiology, Jinling Hospital, Nanjing University School of Medicine; Jing Sun , Department of Radiology, Jinling Hospital, Nanjing University School of Medicine; Min Cao , Department of Radiology, Jinling Hospital, Nanjing University School of Medicine; Guangming Lu, Department of Radiology, Jinling Hospital, Nanjing University School of Medicine; Shuang Xia , Department of Radiology, Tianjin First Central Hospital; Liang Jiang , Department of Radiology, Nanjing First Hospital, Nanjing Medical University; Xindao Yin, Department of Radiology, Nanjing First Hospital, Nanjing Medical University; Jing Ye , Department of Radiology, Northern Jiangsu People's Hospital; Changjie Pan, Department of Radiology,Changzhou No. 2 People’s Hospital Affiliated to Nanjing Medical University; Zhen Jiang , Department of Radiology,The Second Affiliated Hospital of Soochow University; Xiagming Fang, Department of Radiology, the Affiliated Wuxi People's Hospital of Nanjing Medical University; Caifeng Guo, Department of Radiology, The Second Affiliated Hospital of Xuzhou Medical University; Feng Xu , Department of Radiology,Nanjing Gulou Hospital Group Suqian Hospital; Wei Xing , Department of Radiology, Affiliated Third Hospital of Soochow University; Jie Chen , Department of Radiology, Affiliated Third Hospital of Soochow University; Liang Pan , Department of Radiology, Affiliated Third Hospital of Soochow University; Fuqing Zhou, Department of Radiology, The First Affiliated Hospital of Nanchang University

Version:  View help for Version V2

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207725-0001-User_agreement-Restricted_Data_Use_Agreement.pdf application/pdf 454.3 KB 10/30/2024 04:39:AM
示例数据.rar application/x-rar-compressed 5.6 MB 10/24/2024 06:11:PM

Project Citation: 

Zhang, Zhiqiang, Xu, Chuanzhen, Zhou , Yi, Deng , Xin, Liu, Yuying, Cheng, Xiaoqing , … Zhou, Fuqing . Multicenter Acute Ischemic Stroke, MRI and Clinical Text Dataset. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2024-10-30. https://doi.org/10.3886/E207725V2

Project Description

Summary:  View help for Summary Study on the topological feature of infarct lesion and corresponding brain function impairment is of clinical and scientific significance for cerebral stroke. High-quality, large-scale imaging and the matching clinical data are essential for the research. We collected a multimodal MRI dataset of 5788 acute ischaemic stroke patients, which, to the best of our knowledge, is the largest stroke dataset that includes detailed and complete clinical textdata. The release of this dataset is instrumental in facilitating the development of artificial intelligence models aimed at diversifying analytical methodologies. These models explore a number of learnable standardised or repetitive tasks that currently rely on humans, including disease-related scores calculation such as the Aspect score, prognostic prediction, selection of treatment regimens, lesion labelling, and lesion segmentation.
Funding Sources:  View help for Funding Sources National Key Research & Development Program ( 2018YFA0701703)



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