Automated Assessment and Tracking of COVID-19 Pulmonary Disease Severity on Chest Radiographs using Convolutional Siamese Neural Networks

PURPOSE: To develop an automated measure of COVID-19 pulmonary disease severity on chest radiographs (CXRs), for longitudinal disease tracking and outcome prediction. MATERIALS AND METHODS: A convolutional Siamese neural network-based algorithm was trained to output a measure of pulmonary disease se...

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Dettagli Bibliografici
Pubblicato in:Radiol Artif Intell
Autori principali: Li, Matthew D., Arun, Nishanth Thumbavanam, Gidwani, Mishka, Chang, Ken, Deng, Francis, Little, Brent P., Mendoza, Dexter P., Lang, Min, Lee, Susanna I., O’Shea, Aileen, Parakh, Anushri, Singh, Praveer, Kalpathy-Cramer, Jayashree
Natura: Artigo
Lingua:Inglês
Pubblicazione: Radiological Society of North America 2020
Soggetti:
Original Research
Accesso online:https://ncbi.nlm.nih.gov/pmc/articles/PMC7392327/
https://ncbi.nlm.nih.gov/pubmed/33928256
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1148/ryai.2020200079
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