AIMC Topic:
SARS-CoV-2
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"COVID-19 and the epistemology of epidemiological models at the dawn of AI": comment from the editors.
Annals of human biology
Sep 1, 2020
COVID-19 and the epistemology of epidemiological models at the dawn of AI.
Annals of human biology
Sep 1, 2020
The models used to estimate disease transmission, susceptibility and severity determine what epidemiology can (and cannot tell) us about COVID-19. These include: 'model organisms' chosen for their phylogenetic/aetiological similarities; multivariable...
Artificial intelligence technology for diagnosing COVID-19 cases: a review of substantial issues.
European review for medical and pharmacological sciences
Sep 1, 2020
Today, the world suffers from the rapid spread of COVID-19, which has claimed thousands of lives. Unfortunately, its treatment is yet to be developed. Nevertheless, this phenomenon can be decelerated by diagnosing and quarantining patients with COVID...
Massive data initiatives and AI provide testbed for pandemic forecasting.
Nature biotechnology
Sep 1, 2020
Artificial intelligence in ophthalmology during COVID-19 and in the post COVID-19 era.
Current opinion in ophthalmology
Sep 1, 2020
PURPOSE OF REVIEW: To highlight artificial intelligence applications in ophthalmology during the COVID-19 pandemic that can be used to: describe ocular findings and changes correlated with COVID-19; extract information from scholarly articles on SARS...
A review on the use of artificial intelligence for medical imaging of the lungs of patients with coronavirus disease 2019.
Diagnostic and interventional radiology (Ankara, Turkey)
Sep 1, 2020
The results of research on the use of artificial intelligence (AI) for medical imaging of the lungs of patients with coronavirus disease 2019 (COVID-19) has been published in various forms. In this study, we reviewed the AI for diagnostic imaging of ...
Combat COVID-19 with artificial intelligence and big data.
Journal of travel medicine
Aug 20, 2020
A Weakly-Supervised Framework for COVID-19 Classification and Lesion Localization From Chest CT.
IEEE transactions on medical imaging
Aug 1, 2020
Accurate and rapid diagnosis of COVID-19 suspected cases plays a crucial role in timely quarantine and medical treatment. Developing a deep learning-based model for automatic COVID-19 diagnosis on chest CT is helpful to counter the outbreak of SARS-C...
Image Interpretation, Computer-Assisted
Aged
Thorax
Aged, 80 and over
Betacoronavirus
Child
Young Adult
Retrospective Studies
Pneumonia, Viral
Supervised Machine Learning
Adult
Tomography, X-Ray Computed
Coronavirus Infections
Male
Female
Humans
SARS-CoV-2
Middle Aged
Pandemics
Lung
COVID-19
Adolescent
Relational Modeling for Robust and Efficient Pulmonary Lobe Segmentation in CT Scans.
IEEE transactions on medical imaging
Aug 1, 2020
Pulmonary lobe segmentation in computed tomography scans is essential for regional assessment of pulmonary diseases. Recent works based on convolution neural networks have achieved good performance for this task. However, they are still limited in ca...
A Noise-Robust Framework for Automatic Segmentation of COVID-19 Pneumonia Lesions From CT Images.
IEEE transactions on medical imaging
Aug 1, 2020
Segmentation of pneumonia lesions from CT scans of COVID-19 patients is important for accurate diagnosis and follow-up. Deep learning has a potential to automate this task but requires a large set of high-quality annotations that are difficult to col...
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