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Radiology. Artificial Intelligence|April 30, 2021
Automated Assessment and Tracking of COVID-19 Pulmonary Disease Severity on Chest Radiographs using Convolutional Siamese Neural NetworksMatthew D Li, Nishanth Thumbavanam Arun, Mishka Gidwani, et al.
NEJM Evidence|May 30, 2024
Intranasal Oxytocin for ObesityFranziska Plessow, Liya Kerem, Marie-Louis Wronski, et al.
Journal of Intensive Care Medicine|March 30, 2021
Right Ventricular Strain Is Common in Intubated COVID-19 Patients and Does Not Reflect Severity of Respiratory IllnessLauren E Gibson, Raffaele Di Fenza, Min Lang, et al.
Radiology|July 17, 2020
Racial and Ethnic Disparities in Disease Severity on Admission Chest Radiographs among Patients Admitted with Confirmed Coronavirus Disease 2019: A Retrospective Cohort StudyNicholos P Joseph, Nicholas J Reid, Avik Som, et al.
NPJ Digital Medicine|April 8, 2020
Siamese neural networks for continuous disease severity evaluation and change detection in medical imagingMatthew D Li, Ken Chang, Ben Bearce, et al.
Academic Radiology|September 25, 2021
AUR-RRA Review: Logistics of Academic-Industry Partnerships in Artificial IntelligenceBenjamin Spilseth, Colin D McKnight, Matthew D Li, et al.
The Journal of Pediatrics|February 12, 2017
Brain Perfusion and Diffusion Abnormalities in Children Treated for Posterior Fossa Brain TumorsMatthew D Li, Nils D Forkert, Palak Kundu, et al.
Arthritis Care & Research|March 21, 2022
Assessing the Severity of COVID-19 Lung Injury in Rheumatic Diseases Versus the General Population Using Deep Learning-Derived Chest Radiograph ScoresNaomi J Patel, Kristin M D'Silva, Matthew D Li, et al.
Medicine|July 22, 2022
Multi-population generalizability of a deep learning-based chest radiograph severity score for COVID-19Matthew D Li, Nishanth T Arun, Mehak Aggarwal, et al.
Medrxiv : the Preprint Server for Health Sciences|September 30, 2020
Improvement and Multi-Population Generalizability of a Deep Learning-Based Chest Radiograph Severity Score for COVID-19Matthew D Li, Nishanth T Arun, Mehak Aggarwal, et al.
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