AIMC Topic:
SARS-CoV-2
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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...
Deep learning applications to combat the dissemination of COVID-19 disease: a review.
European review for medical and pharmacological sciences
Nov 1, 2020
Recent Coronavirus (COVID-19) is one of the respiratory diseases, and it is known as fast infectious ability. This dissemination can be decelerated by diagnosing and quarantining patients with COVID-19 at early stages, thereby saving numerous lives. ...
Deus Ex Machina? Predicting SARS-CoV-2 Infection from Lab Tests Using Machine Learning.
Clinical chemistry
Nov 1, 2020
Blood Cell Count
Clinical Laboratory Techniques
Betacoronavirus
Pneumonia, Viral
Electronic Health Records
SARS-CoV-2
Reverse Transcriptase Polymerase Chain Reaction
Coronavirus Infections
COVID-19 Testing
Programming Languages
Laboratories
Probability
Machine Learning
Pandemics
COVID-19
Algorithms
Humans
Detection of COVID-19 Using Deep Learning Algorithms on Chest Radiographs.
Journal of thoracic imaging
Nov 1, 2020
PURPOSE: To evaluate the performance of a deep learning (DL) algorithm for the detection of COVID-19 on chest radiographs (CXR).
A Novel Machine Learning-derived Radiomic Signature of the Whole Lung Differentiates Stable From Progressive COVID-19 Infection: A Retrospective Cohort Study.
Journal of thoracic imaging
Nov 1, 2020
OBJECTIVE: This study aimed to use the radiomics signatures of a machine learning-based tool to evaluate the prognosis of patients with coronavirus disease 2019 (COVID-19) infection.
The toll of noninfected CRS patients to the COVID-19 pandemic.
Rhinology
Oct 1, 2020
Social distancing with the aim of avoiding infections and pre-serve critical care capacities during the COVID-19 pandemic has been implemented in Germany according to World Health Organization (WHO) recommendations from early March onwards. Limitatio...
What artificial intelligence may, or may not, contribute to human ARTs.
Journal of assisted reproduction and genetics
Oct 1, 2020
Usefulness of machine learning in COVID-19 for the detection and prognosis of cardiovascular complications.
Reviews in cardiovascular medicine
Sep 30, 2020
Since January 2020, coronavirus disease 2019 (COVID-19) has rapidly become a global concern, and its cardiovascular manifestations have highlighted the need for fast, sensitive and specific tools for early identification and risk stratification. Mach...
Survival Analysis of COVID-19 Patients in Russia Using Machine Learning.
Studies in health technology and informatics
Sep 4, 2020
The current pandemic can likely have several waves and will require a major effort to save lives and provide optimal treatment. The efficient clinical resource planning and efficient treatment require identification of risk groups and specific clinic...
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