AIMC Topic: COVID-19

Clear Filters Showing 2281 to 2290 of 2468 articles

CNN Features and Optimized Generative Adversarial Network for COVID-19 Detection from Chest X-Ray Images.

Critical reviews in biomedical engineering
Coronavirus is a RNA type virus, which makes various respiratory infections in both human as well as animals. In addition, it could cause pneumonia in humans. The Coronavirus affected patients has been increasing day to day, due to the wide spread of...

A Deep Learning based Solution (Covi-DeteCT) Amidst COVID-19.

Current medical imaging
BACKGROUND: The whole world has been severely affected due to the COVID-19 pandemic. The rapid and large-scale spread has caused immense pressure on the medical sector hence increasing the chances of false detection due to human errors and mishandlin...

Detection of COVID-19 Infection in CT and X-ray images using transfer learning approach.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: The infection caused by the SARS-CoV-2 (COVID-19) pandemic is a threat to human lives. An early and accurate diagnosis is necessary for treatment.

Accuracy of the Traditional COVID-19 Phone Triaging System and Phone Triage-Driven Deep Learning Model.

Journal of primary care & community health
OBJECTIVES: During the COVID-19 pandemic, a quick and reliable phone-triage system is critical for early care and efficient distribution of hospital resources. The study aimed to assess the accuracy of the traditional phone-triage system and phone tr...

A Deep Learning Approach to Identify Chest Computed Tomography Features for Prediction of SARS-CoV-2 Infection Outcomes.

Methods in molecular biology (Clifton, N.J.)
There is still an urgent need to develop effective treatments to help minimize the cases of severe COVID-19. A number of tools have now been developed and applied to address these issues, such as the use of non-contrast chest computed tomography (CT)...

A Hybrid Protocol for Identifying Comorbidity-Based Potential Drugs for COVID-19 Using Biomedical Literature Mining, Network Analysis, and Deep Learning.

Methods in molecular biology (Clifton, N.J.)
Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) has spread on an unprecedented scale around the globe. Despite of 141,975 published papers on COVID-19 and several hundreds of new studies carri...

An interpretable multi-task system for clinically applicable COVID-19 diagnosis using CXR.

Journal of X-ray science and technology
BACKGROUND: With the emergence of continuously mutating variants of coronavirus, it is urgent to develop a deep learning model for automatic COVID-19 diagnosis at early stages from chest X-ray images. Since laboratory testing is time-consuming and re...

Pre- and Post-publication Verification for Reproducible Data Mining in Macromolecular Crystallography.

Methods in molecular biology (Clifton, N.J.)
Like an article narrative is deemed by an editor and referees to be worthy of being a version of record on acceptance as a publication, so must the underpinning data also be scrutinized before passing it as a version of record. Indeed without the und...

Development and Applications of Interoperable Biomedical Ontologies for Integrative Data and Knowledge Representation and Multiscale Modeling in Systems Medicine.

Methods in molecular biology (Clifton, N.J.)
The data FAIR Guiding Principles state that all data should be Findable, Accessible, Interoperable, and Reusable. Ontology is critical to data integration, sharing, and analysis. Given thousands of ontologies have been developed in the era of artific...

Optimized chest X-ray image semantic segmentation networks for COVID-19 early detection.

Journal of X-ray science and technology
BACKGROUND: Although detection of COVID-19 from chest X-ray radiography (CXR) images is faster than PCR sputum testing, the accuracy of detecting COVID-19 from CXR images is lacking in the existing deep learning models.