Evaluation of the models generated from clinical features and deep learning-based segmentations: Can thoracic CT on admission help us to predict hospitalized COVID-19 patients who will require intensive care?

Evaluation of the models generated from clinical features and deep learning-based segmentations: Can thoracic CT on admission help us to predict hospitalized COVID-19 patients who will require intensive care?

Abstract Background The aim of the study was to predict the probability of intensive care unit (ICU) care for inpatient COVID-19 cases using clinical and artificial intelligence segmentation-based volumetric and CT-radiomics parameters on admission. Methods Twenty-eight clinical/laboratory features,...

Full description

Bibliographic Details
Main Authors: Mutlu Gülbay, Aliye Baştuğ, Erdem Özkan, Büşra Yüce Öztürk, Bökebatur Ahmet Raşit Mendi, Hürrem Bodur
Format: Article
Language:English
Published: BMC 2022-06-01
Series:BMC Medical Imaging
Subjects:
COVID-19
Deep learning
Artificial intelligence
Computed tomography
Radiomics
Machine learning
Online Access:https://doi.org/10.1186/s12880-022-00833-2

Internet

https://doi.org/10.1186/s12880-022-00833-2

Similar Items