Co-Authors
This is a "connection" page, showing publications co-authored by Matthew Li and Dexter Mendoza.
Connection Strength
0.792
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Multi-Radiologist User Study for Artificial Intelligence-Guided Grading of COVID-19 Lung Disease Severity on Chest Radiographs. Acad Radiol. 2021 04; 28(4):572-576.
Score: 0.231
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Automated Assessment and Tracking of COVID-19 Pulmonary Disease Severity on Chest Radiographs using Convolutional Siamese Neural Networks. Radiol Artif Intell. 2020 Jul; 2(4):e200079.
Score: 0.223
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Severity of Chest Imaging is Correlated with Risk of Acute Neuroimaging Findings among Patients with COVID-19. AJNR Am J Neuroradiol. 2021 05; 42(5):831-837.
Score: 0.058
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Detection of Unsuspected Coronavirus Disease 2019 Cases by Computed Tomography and Retrospective Implementation of the Radiological Society of North America/Society of Thoracic Radiology/American College of Radiology Consensus Guidelines. J Thorac Imaging. 2020 Nov 01; 35(6):346-353.
Score: 0.057
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Implementation of the Radiological Society of North America Expert Consensus Guidelines on Reporting Chest CT Findings Related to COVID-19: A Multireader Performance Study. Radiol Cardiothorac Imaging. 2020 Oct; 2(5):e200276.
Score: 0.056
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Racial and Ethnic Disparities in Disease Severity on Admission Chest Radiographs among Patients Admitted with Confirmed Coronavirus Disease 2019: A Retrospective Cohort Study. Radiology. 2020 12; 297(3):E303-E312.
Score: 0.056
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Pulmonary Vascular Manifestations of COVID-19 Pneumonia. Radiol Cardiothorac Imaging. 2020 Jun; 2(3):e200277.
Score: 0.055
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Hypoxaemia related to COVID-19: vascular and perfusion abnormalities on dual-energy CT. Lancet Infect Dis. 2020 12; 20(12):1365-1366.
Score: 0.055