Deep Learning-Based Automatic Assessment of Lung Impairment in COVID-19 Pneumonia: Predicting Markers of Hypoxia With Computer Vision

Deep Learning-Based Automatic Assessment of Lung Impairment in COVID-19 Pneumonia: Predicting Markers of Hypoxia With Computer Vision

BackgroundHypoxia is a potentially life-threatening condition that can be seen in pneumonia patients.ObjectiveWe aimed to develop and test an automatic assessment of lung impairment in COVID-19 associated pneumonia with machine learning regression models that predict markers of respiratory and cardi...

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Bibliographic Details
Main Authors: Yauhen Statsenko, Tetiana Habuza, Tatsiana Talako, Mikalai Pazniak, Elena Likhorad, Aleh Pazniak, Pavel Beliakouski, Juri G. Gelovani, Klaus Neidl-Van Gorkom, Taleb M. Almansoori, Fatmah Al Zahmi, Dana Sharif Qandil, Nazar Zaki, Sanaa Elyassami, Anna Ponomareva, Tom Loney, Nerissa Naidoo, Guido Hein Huib Mannaerts, Jamal Al Koteesh, Milos R. Ljubisavljevic, Karuna M. Das
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-07-01
Series:Frontiers in Medicine
Subjects:
blended machine learning model
deep learning
COVID-19
pneumonia
SARC-CoV-2
lung structural changes
Online Access:https://www.frontiersin.org/articles/10.3389/fmed.2022.882190/full

Internet

https://www.frontiersin.org/articles/10.3389/fmed.2022.882190/full

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