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
Autores principales: Mungmunpuntipantip, Rujittika, Wiwanitkit, Viroj
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/PMC8256794/
https://www.ncbi.nlm.nih.gov/pubmed/34224062
http://dx.doi.org/10.1007/s11604-021-01169-7
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author Mungmunpuntipantip, Rujittika
Wiwanitkit, Viroj
author_facet Mungmunpuntipantip, Rujittika
Wiwanitkit, Viroj
author_sort Mungmunpuntipantip, Rujittika
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spelling pubmed-82567942021-07-06 Letter to the Editor: Quantitative evaluation of COVID-19 pneumonia severity by CT pneumonia analysis algorithm using deep learning technology and blood test results Mungmunpuntipantip, Rujittika Wiwanitkit, Viroj Jpn J Radiol Letter to the Editor Springer Singapore 2021-07-05 2021 /pmc/articles/PMC8256794/ /pubmed/34224062 http://dx.doi.org/10.1007/s11604-021-01169-7 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
Mungmunpuntipantip, Rujittika
Wiwanitkit, Viroj
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 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 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 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 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 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 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/PMC8256794/
https://www.ncbi.nlm.nih.gov/pubmed/34224062
http://dx.doi.org/10.1007/s11604-021-01169-7
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AT wiwanitkitviroj lettertotheeditorquantitativeevaluationofcovid19pneumoniaseveritybyctpneumoniaanalysisalgorithmusingdeeplearningtechnologyandbloodtestresults

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