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AI and the Infectious Medicine of COVID-19

Vardan, A.; Anthony, P.; Yakimovich, A.


Coinciding with the global pandemic of SARS-CoV-2 and the resulting global public health crisis caused by COVID-19, artificial intelligence methods started playing an ever more important role in Infectious Medicine. On one hand this was a result of a continuous digital transformation of Infectious Medicine—a trend started decades ago. On the other hand, the pandemic catalyzed the adoption of artificial intelligence and other digital and quantitative techniques by Infectious Medicine. In this chapter we review recent works touching upon aspects of COVID-19 patient journey and how it interconnects with big data and artificial intelligence. These include early and clinical research, epidemiology and detection, diagnostics, clinical care and decision support, as well as long-term care and prevention. We cross-compare the published works and assess their maturity. Finally, we provide a conclusion on the state of artificial intelligence in the Infectious Medicine of COVID-19 and attempt a future perspective.

Keywords: SARS-CoV-2; Machine learning; Deep learning; Patient journey; Sequence; Biomedical image; Diagnostics


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