Accuracy of artificial intelligence CT quantification in predicting COVID-19 subjects’ prognosis

Artificial intelligence (AI)-aided analysis of chest CT expedites the quantification of abnormalities and may facilitate the diagnosis and assessment of the prognosis of subjects with COVID-19. This study investigates the performance of an AI-aided quantification model in predicting the clinical out...

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Vydáno v:	PloS one Ročník 18; číslo 12; s. e0294899
Hlavní autoři:	Arian, Arvin, Mehrabi Nejad, Mohammad-Mehdi, Zoorpaikar, Mostafa, Hasanzadeh, Navid, Sotoudeh-Paima, Saman, Kolahi, Shahriar, Gity, Masoumeh, Soltanian-Zadeh, Hamid
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	United States Public Library of Science 08.12.2023 Public Library of Science (PLoS)
Témata:	Abnormalities Accuracy Analysis Artificial intelligence Automation Care and treatment Clinical outcomes Comorbidity Comparative analysis Computed tomography Correlation coefficient Correlation coefficients COVID-19 CT imaging Data collection Datasets Deep learning Diagnosis Health aspects Human error Image analysis Image processing Infections Infectious diseases Lungs Medical imaging Medical imaging equipment Medical prognosis Oxygen content Parenchyma Prognosis Regression analysis Iran
ISSN:	1932-6203, 1932-6203
On-line přístup:	Získat plný text
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