AIMC Topic:
SARS-CoV-2
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A Rapid, Accurate and Machine-Agnostic Segmentation and Quantification Method for CT-Based COVID-19 Diagnosis.
IEEE transactions on medical imaging
Aug 1, 2020
COVID-19 has caused a global pandemic and become the most urgent threat to the entire world. Tremendous efforts and resources have been invested in developing diagnosis, prognosis and treatment strategies to combat the disease. Although nucleic acid ...
Inf-Net: Automatic COVID-19 Lung Infection Segmentation From CT Images.
IEEE transactions on medical imaging
Aug 1, 2020
Coronavirus Disease 2019 (COVID-19) spread globally in early 2020, causing the world to face an existential health crisis. Automated detection of lung infections from computed tomography (CT) images offers a great potential to augment the traditional...
Dual-Sampling Attention Network for Diagnosis of COVID-19 From Community Acquired Pneumonia.
IEEE transactions on medical imaging
Aug 1, 2020
The coronavirus disease (COVID-19) is rapidly spreading all over the world, and has infected more than 1,436,000 people in more than 200 countries and territories as of April 9, 2020. Detecting COVID-19 at early stage is essential to deliver proper h...
Accurate Screening of COVID-19 Using Attention-Based Deep 3D Multiple Instance Learning.
IEEE transactions on medical imaging
Aug 1, 2020
Automated Screening of COVID-19 from chest CT is of emergency and importance during the outbreak of SARS-CoV-2 worldwide in 2020. However, accurate screening of COVID-19 is still a massive challenge due to the spatial complexity of 3D volumes, the la...
Prior-Attention Residual Learning for More Discriminative COVID-19 Screening in CT Images.
IEEE transactions on medical imaging
Aug 1, 2020
We propose a conceptually simple framework for fast COVID-19 screening in 3D chest CT images. The framework can efficiently predict whether or not a CT scan contains pneumonia while simultaneously identifying pneumonia types between COVID-19 and Inte...
Developing a curriculum in artificial intelligence for emergency radiology.
Emergency radiology
Aug 1, 2020
An artificial intelligence approach to COVID-19 infection risk assessment in virtual visits: A case report.
Journal of the American Medical Informatics Association : JAMIA
Aug 1, 2020
OBJECTIVE: In an effort to improve the efficiency of computer algorithms applied to screening for coronavirus disease 2019 (COVID-19) testing, we used natural language processing and artificial intelligence-based methods with unstructured patient dat...
SARS-CoV-2
Risk Assessment
Deep Learning
ROC Curve
Humans
Pandemics
Organizational Case Studies
Neural Networks, Computer
COVID-19
Artificial Intelligence
Algorithms
South Carolina
Natural Language Processing
Clinical Laboratory Techniques
Electronic Health Records
Betacoronavirus
Coronavirus Infections
Pneumonia, Viral
Telemedicine
COVID-19 Testing
Role of 5G-powered remote robotic ultrasound during the COVID-19 outbreak: insights from two cases.
European review for medical and pharmacological sciences
Jul 1, 2020
The 2019 Novel Coronavirus disease (COVID-19) broke out in Wuhan, China in December 2019 and spread throughout the world. Early screening and early diagnosis play key roles in prevention and management of the epidemic. Attention should also be paid t...
Using Machine Learning to Estimate Unobserved COVID-19 Infections in North America.
The Journal of bone and joint surgery. American volume
Jul 1, 2020
BACKGROUND: The detection of coronavirus disease 2019 (COVID-19) cases remains a huge challenge. As of April 22, 2020, the COVID-19 pandemic continues to take its toll, with >2.6 million confirmed infections and >183,000 deaths. Dire projections are ...
Unsupervised Machine Learning for the Discovery of Latent Clusters in COVID-19 Patients Using Electronic Health Records.
Studies in health technology and informatics
Jun 26, 2020
The goal of this paper was to apply unsupervised machine learning techniques towards the discovery of latent clusters in COVID-19 patients. Over 6,000 adult patients tested positive for the SARS-CoV-2 infection at the Mount Sinai Health System in New...
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