On the Centrality of Data: Data Resources in Radiologic Artificial Intelligence-Reference-Cited by-同舟云学术

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On the Centrality of Data: Data Resources in Radiologic Artificial Intelligence

Published:2023-09-01 Issue:5 Volume:5 Page:
ISSN:2638-6100
Container-title:Radiology: Artificial Intelligence
language:en
Short-container-title:Radiology: Artificial Intelligence

Author:

Mongan John¹^ORCID,Halabi Safwan S.¹^ORCID

Affiliation:

1. From the Department of Radiology and Biomedical Imaging; Center for Intelligent Imaging, University of California San Francisco, 505 Parnassus Ave, Room M-391, San Francisco, CA 94143 (J.M.); and Department of Medical Imaging, Ann & Robert H. Lurie Children’s Hospital of Chicago, Chicago, Ill (S.S.H.).

Publisher

Radiological Society of North America (RSNA)

Subject

Artificial Intelligence,Radiology, Nuclear Medicine and imaging,Radiological and Ultrasound Technology

Link

http://pubs.rsna.org/doi/pdf/10.1148/ryai.230231

Reference13 articles.

1. Construction of a Machine Learning Dataset through Collaboration: The RSNA 2019 Brain CT Hemorrhage Challenge

2. The RSNA Pulmonary Embolism CT Dataset

3. The University of California San Francisco Preoperative Diffuse Glioma MRI Dataset

4. Augmenting the National Institutes of Health Chest Radiograph Dataset with Expert Annotations of Possible Pneumonia

5. Curation of the CANDID-PTX Dataset with Free-Text Reports

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Data Resources: Milestones and Building Blocks;Radiology: Artificial Intelligence;2023-11-01

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