AIMC Topic: Betacoronavirus
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Using Artificial Intelligence to Detect COVID-19 and Community-acquired Pneumonia Based on Pulmonary CT: Evaluation of the Diagnostic Accuracy.
Radiology
Mar 19, 2020
Background Coronavirus disease 2019 (COVID-19) has widely spread all over the world since the beginning of 2020. It is desirable to develop automatic and accurate detection of COVID-19 using chest CT. Purpose To develop a fully automatic framework to...
ROC Curve
Imaging, Three-Dimensional
Diagnosis, Differential
Artificial Intelligence
Radiographic Image Interpretation, Computer-Assisted
Pandemics
Pneumonia, Viral
Coronavirus Infections
COVID-19
Retrospective Studies
Sensitivity and Specificity
Tomography, X-Ray Computed
COVID-19 Testing
Male
Female
Community-Acquired Infections
Middle Aged
SARS-CoV-2
Clinical Laboratory Techniques
Deep Learning
Aged
Betacoronavirus
Adult
Humans
Identification of COVID-19 can be quicker through artificial intelligence framework using a mobile phone-based survey when cities and towns are under quarantine.
Infection control and hospital epidemiology
Mar 3, 2020
We propose the use of a machine learning algorithm to improve possible COVID-19 case identification more quickly using a mobile phone-based web survey. This method could reduce the spread of the virus in susceptible populations under quarantine.
The Role of Augmented Intelligence (AI) in Detecting and Preventing the Spread of Novel Coronavirus.
Journal of medical systems
Feb 4, 2020
Drug repurposing targeting COVID-19 3CL protease using molecular docking and machine learning regression approaches.
Scientific reports
May 28, 2025
The COVID-19 pandemic has initiated a global health emergency, with an exigent need for an effective cure. Progressively, drug repurposing is emerging as a promising solution for saving time, cost, and labor. However, the number of drug candidates th...
[Chest radiological lesions in COVID-19 : from classical imaging to artificial intelligence].
Revue medicale de Liege
May 13, 2025
In the course of the pandemic induced by the appearance of a new coronavirus (SARS-CoV-2; COVID-19) causing acute respiratory distress syndrome (ARDS), we had to rethink the diagnostic approach for patients suffering from respiratory symptoms. Indeed...
Antiviral Effectiveness, Clinical Outcomes, and Artificial Intelligence Imaging Analysis for Hospitalized COVID-19 Patients Receiving Antivirals.
Influenza and other respiratory viruses
Sep 1, 2024
INTRODUCTION: There is still a lack of clinical evidence comprehensively evaluating the effectiveness of antiviral treatments for COVID-19 hospitalized patients.
Ritonavir
Aged
Retrospective Studies
Adult
COVID-19 Drug Treatment
Tomography, X-Ray Computed
Lung
Male
Betacoronavirus
Female
Middle Aged
Antiviral Agents
Pneumonia, Viral
SARS-CoV-2
Treatment Outcome
Hospitalization
Humans
Drug Combinations
Artificial Intelligence
Coronavirus Infections
Pandemics
COVID-19
[Identifying Novel Coronavirus Pneumonia With CT Images: A Deep Learning Approach With Detail Upsampling and Attention Guidance].
Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition
Mar 20, 2024
OBJECTIVE: To construct a deep learning-based target detection method to help radiologists perform rapid diagnosis of lesions in the CT images of patients with novel coronavirus pneumonia (NCP) by restoring detailed information and mining local infor...
DKCNN: Improving deep kernel convolutional neural network-based COVID-19 identification from CT images of the chest.
Journal of X-ray science and technology
Jan 1, 2024
BACKGROUND: An efficient deep convolutional neural network (DeepCNN) is proposed in this article for the classification of Covid-19 disease.
DDA-SSNets: Dual decoder attention-based semantic segmentation networks for COVID-19 infection segmentation and classification using chest X-Ray images.
Journal of X-ray science and technology
Jan 1, 2024
BACKGROUND: COVID-19 needs to be diagnosed and staged to be treated accurately. However, prior studies' diagnostic and staging abilities for COVID-19 infection needed to be improved. Therefore, new deep learning-based approaches are required to aid r...
Retrospective analysis of the accuracy of predicting the alert level of COVID-19 in 202 countries using Google Trends and machine learning.
Journal of global health
Dec 1, 2020
BACKGROUND: Internet search engine data, such as Google Trends, was shown to be correlated with the incidence of COVID-19, but only in several countries. We aim to develop a model from a small number of countries to predict the epidemic alert level i...
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