AIMC Topic: Coronavirus Infections
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Main factors influencing recovery in MERS Co-V patients using machine learning.
Journal of infection and public health
Apr 10, 2019
BACKGROUND: Middle East Respiratory Syndrome (MERS) is a major infectious disease which has affected the Middle Eastern countries, especially the Kingdom of Saudi Arabia (KSA) since 2012. The high mortality rate associated with this disease has been ...
Humans
Middle East Respiratory Syndrome Coronavirus
Machine Learning
Survival
Health Personnel
Regression Analysis
Male
Female
Bayes Theorem
Middle Aged
Aged
Coronavirus Infections
Infant
Young Adult
Severity of Illness Index
Multivariate Analysis
Adult
Saudi Arabia
Adolescent
Child, Preschool
Child
Support Vector Machine
Evaluation of a peroxygen-based disinfectant for inactivation of porcine epidemic diarrhea virus at low temperatures on metal surfaces.
Veterinary microbiology
Dec 27, 2017
Porcine epidemic diarrhea virus (PEDV) spread rapidly across the United States in part due to contaminated livestock trailers. The objective of this study was to test a peroxygen-based disinfectant for the ability to inactivate PEDV on aluminum surfa...
Large-scale machine learning of media outlets for understanding public reactions to nation-wide viral infection outbreaks.
Methods (San Diego, Calif.)
Aug 13, 2017
From May to July 2015, there was a nation-wide outbreak of Middle East respiratory syndrome (MERS) in Korea. MERS is caused by MERS-CoV, an enveloped, positive-sense, single-stranded RNA virus belonging to the family Coronaviridae. Despite expert opi...
[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.
Aged
Adult
Male
Middle Aged
Tomography, X-Ray Computed
Humans
Female
Artificial Intelligence
SARS-CoV-2
Pandemics
Hospitalization
Coronavirus Infections
COVID-19
Ritonavir
Retrospective Studies
COVID-19 Drug Treatment
Lung
Betacoronavirus
Antiviral Agents
Pneumonia, Viral
Treatment Outcome
Drug Combinations
[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...
Latent COVID-19 Clusters in Patients with Chronic Respiratory Conditions.
Studies in health technology and informatics
Nov 23, 2020
The goal of this paper was to apply unsupervised machine learning techniques towards the discovery of latent COVID-19 clusters in patients with chronic lower respiratory diseases (CLRD). Patients who underwent testing for SARS-CoV-2 were identified f...
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