Reply to the Letter to the Editor: Quantitative evaluation of COVID-19 pneumonia severity by CT pneumonia analysis algorithm using deep learning technology and blood test results

Detalles Bibliográficos
Autor principal: Okuma, Tomohisa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Singapore 2021
Materias:
Letter to the Editor
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8294244/
https://www.ncbi.nlm.nih.gov/pubmed/34287738
http://dx.doi.org/10.1007/s11604-021-01179-5
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author Okuma, Tomohisa
author_facet Okuma, Tomohisa
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spelling pubmed-82942442021-07-21 Reply to the Letter to the Editor: Quantitative evaluation of COVID-19 pneumonia severity by CT pneumonia analysis algorithm using deep learning technology and blood test results Okuma, Tomohisa Jpn J Radiol Letter to the Editor Springer Singapore 2021-07-21 2021 /pmc/articles/PMC8294244/ /pubmed/34287738 http://dx.doi.org/10.1007/s11604-021-01179-5 Text en © Japan Radiological Society 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Letter to the Editor
Okuma, Tomohisa
Reply to the Letter to the Editor: Quantitative evaluation of COVID-19 pneumonia severity by CT pneumonia analysis algorithm using deep learning technology and blood test results
title Reply to the Letter to the Editor: Quantitative evaluation of COVID-19 pneumonia severity by CT pneumonia analysis algorithm using deep learning technology and blood test results
title_full Reply to the Letter to the Editor: Quantitative evaluation of COVID-19 pneumonia severity by CT pneumonia analysis algorithm using deep learning technology and blood test results
title_fullStr Reply to the Letter to the Editor: Quantitative evaluation of COVID-19 pneumonia severity by CT pneumonia analysis algorithm using deep learning technology and blood test results
title_full_unstemmed Reply to the Letter to the Editor: Quantitative evaluation of COVID-19 pneumonia severity by CT pneumonia analysis algorithm using deep learning technology and blood test results
title_short Reply to the Letter to the Editor: Quantitative evaluation of COVID-19 pneumonia severity by CT pneumonia analysis algorithm using deep learning technology and blood test results
title_sort reply to the letter to the editor: quantitative evaluation of covid-19 pneumonia severity by ct pneumonia analysis algorithm using deep learning technology and blood test results
topic Letter to the Editor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8294244/
https://www.ncbi.nlm.nih.gov/pubmed/34287738
http://dx.doi.org/10.1007/s11604-021-01179-5
work_keys_str_mv AT okumatomohisa replytothelettertotheeditorquantitativeevaluationofcovid19pneumoniaseveritybyctpneumoniaanalysisalgorithmusingdeeplearningtechnologyandbloodtestresults

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