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Association of AI quantified COVID-19 chest CT and patient outcome
2021
International Journal of Computer Assisted Radiology and Surgery
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This study aims to develop artificial intelligence (AI)-based methods to quantify disease severity and predict COVID-19 patient outcome. ...
The computed severity scores achieved better performance than radiologists in predicting COVID-19 patient outcome by consistently quantifying image features. ...
Acknowledgements This work was partially supported by National Institute of Biomedical Imaging and Bioengineering (NIBIB) under award R21EB028001 and National Heart, Lung, and Blood Institute (NHLBI) under ...
doi:10.1007/s11548-020-02299-5
pmid:33484428
fatcat:c656gp3pbngc5ptdwwind6wmkm
Prediction of disease progression in patients with COVID-19 by artificial intelligence assisted lesion quantification
2020
Scientific Reports
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To investigate the value of artificial intelligence (AI) assisted quantification on initial chest CT for prediction of disease progression and clinical outcome in patients with coronavirus disease 2019 ...
Consolidation volume quantified on initial chest CT was the strongest predictor for disease severity progression and larger consolidation volume was associated with unfavorable clinical outcome. ...
AI-assisted lesion quantification was helpful for risk stratification and prognosis evaluation in patients with COVID-19. ...
doi:10.1038/s41598-020-79097-1
pmid:33328512
fatcat:rxlhdknaqvf75onq3s5dznap54
Validation of Chest Computed Tomography Artificial Intelligence to Determine the Requirement for Mechanical Ventilation and Risk of Mortality in Hospitalized Coronavirus Disease-19 Patients in a Tertiary Care Center In Mexico City
2020
Revista de investigación clínica
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The proposed prognostic models using biochemical variables and imaging data measured by AI on chest CT showed good risk classification in our population of hospitalized COVID-19 patients. ...
Chest CT images of 166 COVID-19 patients hospitalized from April 1 to 20, 2020, were retrospectively analyzed using AI algorithm software. Data were collected from their medical records. ...
part of the triage process in the CT analysis of COVID-19 patients. ...
doi:10.24875/ric.20000451
pmid:33201872
fatcat:64fb7hh3sjd3lgo2ofmgbrtfja
Automated AI-Driven CT Quantification of Lung Disease Predicts Adverse Outcomes in Patients Hospitalized for COVID-19 Pneumonia
2021
Diagnostics
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or death in patients hospitalized with COVID-19 pneumonia. 323 consecutive patients (mean age 65 ± 15 years, 192 men), with laboratory-confirmed COVID-19 and an abnormal chest CT scan, were admitted to ...
The extent of consolidation and all lung opacities were quantified on an initial CT scan using a 3D automatic AI-based software. ...
Acknowledgments: The authors thank Siemens Healthineers, and particularly Dorin Comaniciu, for providing the AI software for this study. ...
doi:10.3390/diagnostics11050878
pmid:34069115
pmcid:PMC8156322
fatcat:w5cmlnfdqnfgbdm6f65a4tz4v4
AI-Driven COVID-19 Tools to Interpret, Quantify Lung Images
2020
IEEE Pulse
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COVID-19. ...
To that end, several research groups have begun looking to artificial intelligence (AI) as a tool for reading and analyzing X-rays and computed tomography (CT) scans, and helping to diagnose and monitor ...
AI for CT scans CT scans are the focus of icometrix, which has developed AI algorithms, called icolung ( Figure 6 ), to identify COVID-19 and monitor patient progression. ...
doi:10.1109/mpuls.2020.3008354
pmid:32804639
fatcat:hzc3lfafjbhx7anybi4ll6vtdu
Glycemic status affects the severity of coronavirus disease 2019 in patients with diabetes mellitus: an observational study of CT radiological manifestations using an artificial intelligence algorithm
2021
Acta Diabetologica
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COVID-19 disease severity and to investigate the association between CT lesions and clinical outcome. ...
Increased blood glucose level was correlated with the severity of lung involvement, as evidenced by certain chest CT parameters, and clinical prognosis in diabetic COVID-19 patients. ...
Acknowledgements We greatly appreciate the assistance of Jiazheng Wang (Cancer Research UK Cambridge Institute, Li Ka Shing Centre, ...
doi:10.1007/s00592-020-01654-x
pmid:33420614
pmcid:PMC7792916
fatcat:juumgydn45dfxamxvvia3bt2ji
Deep Learning and Its Role in COVID-19 Medical Imaging
2020
Intelligence-Based Medicine
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Given these issues surrounding COVID-19, many groups began to explore the benefits of 'big data' processing and algorithms to assist with the diagnosis and therapeutic development of COVID-19. ...
COVID-19 is one of the greatest global public health challenges in history. ...
Chest X-ray and Chest CT are the two most common imaging studies for diagnosis and management of COVID-19 patients. ...
doi:10.1016/j.ibmed.2020.100013
pmid:33169117
pmcid:PMC7641591
fatcat:xk244y53jnflxnkyts6zex5hfe
Visceral adiposity and severe COVID-19 disease: application of an artificial intelligence algorithm to improve clinical risk prediction
2021
Open Forum Infectious Diseases
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We tested the hypothesis that visceral adipose tissue (VAT) is associated with severe outcomes in patients hospitalized with COVID-19, independent of body mass index (BMI). ...
AI offers a promising approach to routinely ascertain VAT and improve clinical risk prediction in COVID-19. ...
Given that many hospitalized patients with severe COVID-19 have a CT scan of the chest or abdomen performed as part of their clinical work-up, it would be possible to adapt this technology and automate ...
doi:10.1093/ofid/ofab275
pmid:34258315
pmcid:PMC8244656
fatcat:miai4zcotvb6renljfp7julcma
Automated detection and quantification of COVID-19 airspace disease on chest radiographs: A novel approach achieving radiologist-level performance using a CNN trained on digital reconstructed radiographs (DRRs) from CT-based ground-truth
[article]
2020
arXiv
pre-print
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A convolutional neural network (CNN) was trained with DRR images generated from a larger-scale CT dataset of COVID-19 and non-COVID-19 patients, automatically segmenting lungs, AD and quantifying POa on ...
Materials and Methods: We retrospectively selected a cohort of 86 COVID-19 patients (with positive RT-PCR), from March-May 2020 at a tertiary hospital in the northeastern USA, who underwent chest CT and ...
Acknowledgements: We gratefully acknowledge the contributions of multiple frontline hospitals to this collaboration. ...
arXiv:2008.06330v1
fatcat:mijf46mhtfdyreyrk2l4cuhhxa
Quantitative evaluation of COVID-19 pneumonia severity by CT pneumonia analysis algorithm using deep learning technology and blood test results
2021
Japanese Journal of Radiology
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The mean HU total of the whole lung, determined by the AI algorithm, and eGFR reflect the severity of COVID-19 pneumonia. ...
the severity of COVID-19 pneumonia. ...
Given the importance of early detection and severity assessment of COVID-19 pneumonia for timely intervention and optimization of outcomes, an AI-based approach combining quantitative CT image evaluation ...
doi:10.1007/s11604-021-01134-4
pmid:33988788
pmcid:PMC8120249
fatcat:olwsjsd7s5a6dgoerrmmehyvhy
Comparing Visual Scoring of Lung Injury with a Quantifying AI-Based Scoring in Patients with COVID-19
2021
Journal of the Belgian Society of Radiology
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and monitoring of COVID-19 patients. ...
Fast diagnosis of Coronavirus Disease 2019 (COVID-19), and the detection of high-risk patients are crucial but challenging in the pandemic outbreak. ...
[13] , several limitations in the diagnostic analysis of COVID-19 on chest CT must be kept in mind: First, approximately 50% of patients with COVID-19 infection have a normal CT scan if scanned early ...
doi:10.5334/jbsr.2330
pmid:33870080
pmcid:PMC8034398
fatcat:e3t47c7znzajdmiuwasmehzaha
Chest CT in COVID-19 pneumonia: a review of current knowledge
2020
Diagnostic and Interventional Imaging
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The current COVID-19 pandemic has highlighted the essential role of chest computed tomography (CT) examination in patient triage in the emergency departments, allowing them to be referred to "COVID" or ...
Typical CT features consist of bilateral ground-glass opacities with peripheral, posterior and basal predominance. Lung disease extent on CT correlates with clinical severity. ...
outcome of COVID-19 patients. ...
doi:10.1016/j.diii.2020.06.001
pmid:32571748
pmcid:PMC7287482
fatcat:gnkd2wmjyvfprfs2hnnndu4ahi
Factors associated with worsening oxygenation in patient with non-severe COVID-19 pneumonia
2021
Tuberculosis and Respiratory Diseases
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Our study presents initial CT evaluated by AI or visual severity scoring as well as serum markers of inflammation at admission are significantly associated with worsening oxygenation in this COVID-19 pneumonia ...
Parameters were compared, and the extent of viral pneumonia from an initial chest CT were calculated using artificial intelligence (AI) and measured visually by a radiologist. ...
associated with severe and fatal COVID-19 in hospitalised patients 1, 6, 7 . ...
doi:10.4046/trd.2020.0139
pmid:33401345
pmcid:PMC8010417
fatcat:zibksz4lpbbzxoqwpehbcvgrqa
Machine learning based on clinical characteristics and chest CT quantitative measurements for prediction of adverse clinical outcomes in hospitalized patients with COVID-19
2021
European Radiology
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accurate lung involvement quantification on chest CT images. • Machine learning based on clinical and CT variables can facilitate the prediction of adverse outcomes of COVID-19. ...
To develop and validate a machine learning model for the prediction of adverse outcomes in hospitalized patients with COVID-19. ...
(I) Non-severe COVID-19 patients who underwent chest CT scan on admission were included. ...
doi:10.1007/s00330-021-07957-z
pmid:33856514
fatcat:gcffomveyrfmdmjlis47ics5hm
Evolution of CT Findings and Lung Residue in Patients with COVID-19 Pneumonia: Quantitative Analysis of the Disease with a Computer Automatic Tool
2021
Journal of Personalized Medicine
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Purpose: the purpose of this study was to assess the evolution of computed tomography (CT) findings and lung residue in patients with COVID-19 pneumonia, via quantified evaluation of the disease, using ...
Materials and methods: we retrospectively evaluated 341 CT examinations of 140 patients (68 years of median age) infected with COVID-19 (confirmed by real-time reverse transcriptase polymerase chain reaction ...
[5] assessed the chest CT to determine the changes in the findings associated with COVID-19 from initial diagnosis until patient recovery. ...
doi:10.3390/jpm11070641
fatcat:shaxhnxklncatdrped52kgioli
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