Review on Diagnosis of COVID-19 from Chest CT Images Using Artificial Intelligence.
Comput Math Methods Med
; 2020: 9756518, 2020.
Article
in English
| MEDLINE | ID: covidwho-814273
ABSTRACT
The COVID-19 diagnostic approach is mainly divided into two broad categories, a laboratory-based and chest radiography approach. The last few months have witnessed a rapid increase in the number of studies use artificial intelligence (AI) techniques to diagnose COVID-19 with chest computed tomography (CT). In this study, we review the diagnosis of COVID-19 by using chest CT toward AI. We searched ArXiv, MedRxiv, and Google Scholar using the terms "deep learning", "neural networks", "COVID-19", and "chest CT". At the time of writing (August 24, 2020), there have been nearly 100 studies and 30 studies among them were selected for this review. We categorized the studies based on the classification tasks COVID-19/normal, COVID-19/non-COVID-19, COVID-19/non-COVID-19 pneumonia, and severity. The sensitivity, specificity, precision, accuracy, area under the curve, and F1 score results were reported as high as 100%, 100%, 99.62, 99.87%, 100%, and 99.5%, respectively. However, the presented results should be carefully compared due to the different degrees of difficulty of different classification tasks.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Pneumonia, Viral
/
Radiographic Image Interpretation, Computer-Assisted
/
Tomography, X-Ray Computed
/
Coronavirus Infections
/
Clinical Laboratory Techniques
/
Pandemics
/
Betacoronavirus
Type of study:
Diagnostic study
/
Observational study
/
Prognostic study
Limits:
Humans
Language:
English
Journal:
Comput Math Methods Med
Journal subject:
Medical Informatics
Year:
2020
Document Type:
Article
Affiliation country:
2020
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