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                <text>Dominio científico: Coronavirus</text>
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              <text>Contact Tracing in Healthcare Settings During the COVID-19 Pandemic Using Bluetooth Low Energy and Artificial Intelligence—A Viewpoint</text>
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              <text>Guanglin Tang, Kenneth Westover, Steve Jiang</text>
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              <text>The COVID-19 pandemic has inflicted great damage with effects that will likely linger for a long time. This crisis has highlighted the importance of contact tracing in healthcare settings because hospitalized patients are among the high risk for complications and death. Moreover, effective contact tracing schemes are not yet available in healthcare settings. A good contact tracing technology in healthcare settings should be equipped with six features: promptness, simplicity, high precision, integration, minimized privacy concerns, and social fairness. One potential solution that addresses all of these elements leverages an indoor real-time location system based on Bluetooth Low Energy and artificial intelligence.</text>
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              <text>covid-19, contact-tracing, artificial intelligence, deep learning, Bluetooth, real-time location system</text>
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              <text>10.3389/frai.2021.666599</text>
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              <text>Epidemiology and Health</text>
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              <text>Korean Society of Epidemiology</text>
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              <text>Electronic computers. Computer science</text>
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