AIMC Topic: COVID-19 Testing
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Eight pruning deep learning models for low storage and high-speed COVID-19 computed tomography lung segmentation and heatmap-based lesion localization: A multicenter study using COVLIAS 2.0.
Computers in biology and medicine
May 21, 2022
BACKGROUND: COVLIAS 1.0: an automated lung segmentation was designed for COVID-19 diagnosis. It has issues related to storage space and speed. This study shows that COVLIAS 2.0 uses pruned AI (PAI) networks for improving both storage and speed, wilie...
Efficient Framework for Detection of COVID-19 Omicron and Delta Variants Based on Two Intelligent Phases of CNN Models.
Computational and mathematical methods in medicine
Apr 21, 2022
INTRODUCTION: While the COVID-19 pandemic was waning in most parts of the world, a new wave of COVID-19 Omicron and Delta variants in Central Asia and the Middle East caused a devastating crisis and collapse of health-care systems. As the diagnostic ...
An original deep learning model using limited data for COVID-19 discrimination: A multicenter study.
Medical physics
Apr 18, 2022
OBJECTIVES: Artificial intelligence (AI) has been proved to be a highly efficient tool for COVID-19 diagnosis, but the large data size and heavy label force required for algorithm development and the poor generalizability of AI algorithms, to some ex...
An Interpretable Chest CT Deep Learning Algorithm for Quantification of COVID-19 Lung Disease and Prediction of Inpatient Morbidity and Mortality.
Academic radiology
Apr 4, 2022
RATIONALE AND OBJECTIVES: The burden of coronavirus disease 2019 (COVID-19) airspace opacities is time consuming and challenging to quantify on computed tomography. The purpose of this study was to evaluate the ability of a deep convolutional neural ...
Think positive: An interpretable neural network for image recognition.
Neural networks : the official journal of the International Neural Network Society
Apr 4, 2022
The COVID-19 pandemic is an ongoing pandemic and is placing additional burden on healthcare systems around the world. Timely and effectively detecting the virus can help to reduce the spread of the disease. Although, RT-PCR is still a gold standard f...
Factors associated with COVID-19 lethality in a hospital in the Cajamarca region in Peru.
Revista peruana de medicina experimental y salud publica
Apr 1, 2022
OBJECTIVE.: To identify the clinical and epidemiological characteristics related to lethality in patients hospitalized for COVID-19 at the Simón Bolívar Hospital in Cajamarca, during June-August 2020.
Machine Learning with Quantum Seagull Optimization Model for COVID-19 Chest X-Ray Image Classification.
Journal of healthcare engineering
Mar 30, 2022
Early and accurate detection of COVID-19 is an essential process to curb the spread of this deadly disease and its mortality rate. Chest radiology scan is a significant tool for early management and diagnosis of COVID-19 since the virus targets the r...
Automated detection of COVID-19 cases from chest X-ray images using deep neural network and XGBoost.
Radiography (London, England : 1995)
Mar 28, 2022
INTRODUCTION: In late 2019 and after the COVID-19 pandemic in the world, many researchers and scholars tried to provide methods for detecting COVID-19 cases. Accordingly, this study focused on identifying patients with COVID-19 from chest X-ray image...
Deep Learning and Medical Image Analysis for COVID-19 Diagnosis and Prediction.
Annual review of biomedical engineering
Mar 22, 2022
The coronavirus disease 2019 (COVID-19) pandemic has imposed dramatic challenges to health-care organizations worldwide. To combat the global crisis, the use of thoracic imaging has played a major role in the diagnosis, prediction, and management of ...
Human-level COVID-19 diagnosis from low-dose CT scans using a two-stage time-distributed capsule network.
Scientific reports
Mar 22, 2022
Reverse transcription-polymerase chain reaction is currently the gold standard in COVID-19 diagnosis. It can, however, take days to provide the diagnosis, and false negative rate is relatively high. Imaging, in particular chest computed tomography (C...
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