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DeepCOVID-XR: An Artificial Intelligence Algorithm to Detect COVID-19 on Chest Radiographs Trained and Tested on a Large U.S. Clinical Data Set

机译：DeepCovid-XR：一种人工智能算法检测Covid-19胸部射线照相训练和在大型美国临床数据集上测试

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Ramsey M. Wehbe; Jiayue Sheng; Shinjan Dutta; Siyuan Chai; Amil Dravid; Semih Barutcu; Yunan Wu; Donald R. Cantrell; Nicholas Xiao; Bradley D. Allen; Gregory A. MacNealy; Hatice Savas; Rishi Agrawal; Nishant Parekh; Aggelos K. Katsaggelos;
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1. Artificial Intelligence Algorithm Detecting Lung Infection in Supine Chest Radiographs of Critically Ill Patients With a Diagnostic Accuracy Similar to Board-Certified Radiologists [J] . Critical care medicine . 2020,第7期

机译：检测诊断准确性诊断准确性诊断准确性诊断精度的仰卧胸部X射线照片中肺部感染的人工智能算法
2. COVID-19 on Chest Radiographs: A Multireader Evaluation of an Artificial Intelligence System [J] . Murphy Keelin, Smits Henk, Knoops Arnoud J. G., Radiology . 2020,第3期

机译：Covid-19胸部射线照片：人工智能系统的多风格评价
3. Artificial intelligence for the detection of COVID-19 pneumonia on chest CT using multinational datasets [J] . Stephanie A. Harmon, Thomas H. Sanford, Sheng Xu, Nature Communications . 2020,第1期

机译：使用跨国数据集检测胸部CT上Covid-19肺炎的人工智能
4. Classification of COVID-19 in Chest Radiographs: Assessing the Impact of Imaging Parameters using Clinical and Simulated Images [C] . Rafael B. Fricks, Ehsan Abadi, Francesco Ria, Conference on Medical Imaging: Computer-Aided Diagnosis . 2021

机译：Covid-19中Covid-19的分类：使用临床和模拟图像评估成像参数的影响
5. Artificial Intelligence to Accelerate Covid-19 Identification from Chest X-Rays [D] . Adila, Dyah. 2021

机译：从胸部X射线加速Covid-19识别的人工智能
6. Deep transfer learning artificial intelligence accurately stages COVID-19 lung disease severity on portable chest radiographs [O] . Jocelyn Zhu, Beiyi Shen, Almas Abbasi, 2020

机译：深度转移学习人工智能准确阶段在便携式胸部射线照片上阶段Covid-19肺病严重程度
7. The Potential of Artificial Intelligence to Analyze Chest Radiographs for Signs of COVID-19 Pneumonia [O] . Bram van Ginneken 2021

机译：人工智能分析Covid-19肺炎的胸部射线照片的潜力

DeepCOVID-XR: An Artificial Intelligence Algorithm to Detect COVID-19 on Chest Radiographs Trained and Tested on a Large U.S. Clinical Data Set

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