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Big Data and artificial intelligence for translational research in COVID-19: a rapid review

ABSTRACT

The objective of this study was to identify how Artificial Intelligence (AI) has been used for translational research in the context of COVID-19. A rapid review was carried out to identify the use of AI techniques in the translation of technologies to face COVID-19. A search strategy was used based on MeSH terms and their respective synonyms in seven databases. Of the 59 articles identified, eight were included. We identified 11 experiments that used AI for translational research in Covid-19: prediction of drug efficacy; predicting the pathogenicity of SARS-CoV-2; imaging diagnosis for COVID-19; predicting the incidence of COVID-19; estimates of the impact of COVID-19 on society; automation of sanitizing hospital and clinical environments; screening of infected and possibly infected people; monitoring the use of masks; prediction of patient severity; patient risk stratification; and prediction of hospital resources. Translational research can help in productive and industrial development in health, especially when supported by AI methods, an increasingly important tool, especially when discussing the Fourth Industrial Revolution and its applications in health.

KEYWORDS
Translational research, biomedical; Artificial Intelligence; Machine learning; COVID-19

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