Article

Detection of COVID-19 Infection from Routine Blood Exams with Machine Learning: a Feasibility Study

2020-04-25

Abstract excerpt

<h4>Background</h4> The COVID-19 pandemia due to the SARS-CoV-2 coronavirus, in its first 4 months since its outbreak, has to date reached more than 200 countries worldwide with more than 2 million confirmed cases (probably a much higher number of infected), and almost 200,000 deaths. Amplification of viral RNA by (real time) reverse transcription polymerase chain reaction (rRT-PCR) is the current gold standard te...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 91fd4abc-dda0-52a8-b8e4-60c345272d63
DOI: 10.1101/2020.04.22.20075143

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Detection of COVID-19 Infection from Routine Blood Exams with Machine Learning: a Feasibility StudyDOI 10.1101/2020.04.22.20075143Read

Prognosing the Risk of COVID-19 Death Through a Machine Learning-Based Routine Blood PanelSemantic proximity Read

Rapid protocols to support Covid-19 clinical diagnosis based on hematological parametersSemantic proximity Read

Rapid protocols to support Covid-19 clinical diagnosis based on hematological parametersSemantic proximity Read

Machine learning is the key to diagnose COVID-19: a proof of concept study.Semantic proximity Read

A multipurpose machine learning approach to predict COVID-19 negative prognosis in São Paulo, BrazilSemantic proximity Read

COVID-19 Mortality Risk Prediction using Clinical and Laboratory Examination: Machine Learning Approach for ImplementationSemantic proximity Read

Using Machine Learning of Clinical Data to Diagnose COVID-19Semantic proximity Read

Artificial intelligence-enabled rapid diagnosis of COVID-19 patientsSemantic proximity Read

Routine laboratory blood tests predict SARS-CoV-2 infection using machine learningSemantic proximity Read

Rapid assessment of COVID-19 mortality risk with GASS classifiersSemantic proximity Read

Using Automated-Machine Learning to Predict COVID-19 Patient Survival: Identify Influential BiomarkersSemantic proximity Read

Using Machine Learning to assess Covid-19 risksSemantic proximity Read