About: Risk Estimation of SARS-CoV-2 Transmission from Bluetooth Low Energy Measurements

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An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Risk Estimation of SARS-CoV-2 Transmission from Bluetooth Low Energy Measurements
Creator	Fraunhofer, † Ma, Jackie Müller, Klaus-Robert Neumann, David Samek, Wojciech Sattler, Felix Schäfer, Ralf Wagner, Patrick Wenzel, Markus Wiegand, Thomas
Source	ArXiv
abstract	Digital contact tracing approaches based on Bluetooth low energy (BLE) have the potential to efficiently contain and delay outbreaks of infectious diseases such as the ongoing SARS-CoV-2 pandemic. In this work we propose a novel machine learning based approach to reliably detect subjects that have spent enough time in close proximity to be at risk of being infected. Our study is an important proof of concept that will aid the battery of epidemiological policies aiming to slow down the rapid spread of COVID-19.
has issue date	2020-04-22(xsd:dateTime)
has license	arxiv
sha1sum (hex)	69f8afdb80906c6fa3db4367155c300b10c5484a
resource representing a document's title	Risk Estimation of SARS-CoV-2 Transmission from Bluetooth Low Energy Measurements
resource representing a document's body	covid:69f8afdb80906c6fa3db4367155c300b10c5484a#body_text
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