It has been shown that artificial intelligence (AI) may yield rapid and improved detection of coronavirus disease 2019 (COVID-19) by integrating chest CT findings with clinical symptoms, exposure history and laboratory testing (1). Early detection and reduction of workload for healthcare workers have been proposed as main applications of AI in COVID-19 pandemic (2), despite limitations, constraints and pitfalls (3,4).
The challenge of COVID-19 low disease prevalence for artificial intelligence models: report of 1,610 patients / Quattrocchi, Carlo C.; Mallio, Carlo A.; Presti, Gabriele; Beomonte Zobel, Bruno; Cardinale, Jacopo; Iozzino, Mario; Della Sala, Sabino W.. - In: QUANTITATIVE IMAGING IN MEDICINE AND SURGERY. - ISSN 2223-4292. - 10:9(2020), pp. 1891-1893. [10.21037/qims-20-782]
The challenge of COVID-19 low disease prevalence for artificial intelligence models: report of 1,610 patients
Quattrocchi, Carlo C.;
2020-01-01
Abstract
It has been shown that artificial intelligence (AI) may yield rapid and improved detection of coronavirus disease 2019 (COVID-19) by integrating chest CT findings with clinical symptoms, exposure history and laboratory testing (1). Early detection and reduction of workload for healthcare workers have been proposed as main applications of AI in COVID-19 pandemic (2), despite limitations, constraints and pitfalls (3,4).| File | Dimensione | Formato | |
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