AIMC Topic: Pandemics
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Vital signs assessed in initial clinical encounters predict COVID-19 mortality in an NYC hospital system.
Scientific reports
Dec 9, 2020
Timely and effective clinical decision-making for COVID-19 requires rapid identification of risk factors for disease outcomes. Our objective was to identify characteristics available immediately upon first clinical evaluation related COVID-19 mortali...
Detection of Hate Speech in COVID-19-Related Tweets in the Arab Region: Deep Learning and Topic Modeling Approach.
Journal of medical Internet research
Dec 8, 2020
BACKGROUND: The massive scale of social media platforms requires an automatic solution for detecting hate speech. These automatic solutions will help reduce the need for manual analysis of content. Most previous literature has cast the hate speech de...
Development and External Validation of a Machine Learning Tool to Rule Out COVID-19 Among Adults in the Emergency Department Using Routine Blood Tests: A Large, Multicenter, Real-World Study.
Journal of medical Internet research
Dec 2, 2020
BACKGROUND: Conventional diagnosis of COVID-19 with reverse transcription polymerase chain reaction (RT-PCR) testing (hereafter, PCR) is associated with prolonged time to diagnosis and significant costs to run the test. The SARS-CoV-2 virus might lea...
Application of artificial neural networks to predict the COVID-19 outbreak.
Global health research and policy
Nov 23, 2020
BACKGROUND: Millions of people have been infected worldwide in the COVID-19 pandemic. In this study, we aim to propose fourteen prediction models based on artificial neural networks (ANN) to predict the COVID-19 outbreak for policy makers.
Comparison of deep learning with regression analysis in creating predictive models for SARS-CoV-2 outcomes.
BMC medical informatics and decision making
Nov 19, 2020
BACKGROUND: Accurately predicting patient outcomes in Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) could aid patient management and allocation of healthcare resources. There are a variety of methods which can be used to develop progno...
COVID-19 Surveillance in a Primary Care Sentinel Network: In-Pandemic Development of an Application Ontology.
JMIR public health and surveillance
Nov 17, 2020
BACKGROUND: Creating an ontology for COVID-19 surveillance should help ensure transparency and consistency. Ontologies formalize conceptualizations at either the domain or application level. Application ontologies cross domains and are specified thro...
An efficient mixture of deep and machine learning models for COVID-19 diagnosis in chest X-ray images.
PloS one
Nov 17, 2020
A newly emerged coronavirus (COVID-19) seriously threatens human life and health worldwide. In coping and fighting against COVID-19, the most critical step is to effectively screen and diagnose infected patients. Among them, chest X-ray imaging techn...
Machine Learning for Mortality Analysis in Patients with COVID-19.
International journal of environmental research and public health
Nov 12, 2020
This paper analyzes a sample of patients hospitalized with COVID-19 in the region of Madrid (Spain). Survival analysis, logistic regression, and machine learning techniques (both supervised and unsupervised) are applied to carry out the analysis wher...
Analyzing inter-reader variability affecting deep ensemble learning for COVID-19 detection in chest radiographs.
PloS one
Nov 12, 2020
Data-driven deep learning (DL) methods using convolutional neural networks (CNNs) demonstrate promising performance in natural image computer vision tasks. However, their use in medical computer vision tasks faces several limitations, viz., (i) adapt...
Repurposing therapeutics for COVID-19: Rapid prediction of commercially available drugs through machine learning and docking.
PloS one
Nov 12, 2020
BACKGROUND: The outbreak of the novel coronavirus disease COVID-19, caused by the SARS-CoV-2 virus has spread rapidly around the globe during the past 3 months. As the virus infected cases and mortality rate of this disease is increasing exponentiall...
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