Tietueen sitaatit
APA-viiteAllahabadi, H., Amann, J., Balot, I., Beretta, A., Binkley, C., Bozenhard, J., . . . Sciences, A. U. o. A. (2022). Assessing Trustworthy AI in times of COVID-19. Deep Learning for predicting a multi-regional score conveying the degree of lung compromise in COVID-19 patients. Institute of Electrical and Electronics Engineers (IEEE).
Chicago-tyylinen lähdeviittausAllahabadi, Himanshi, et al. Assessing Trustworthy AI in Times of COVID-19. Deep Learning for Predicting a Multi-regional Score Conveying the Degree of Lung Compromise in COVID-19 Patients. Institute of Electrical and Electronics Engineers (IEEE), 2022.
MLA-viiteAllahabadi, Himanshi, et al. Assessing Trustworthy AI in Times of COVID-19. Deep Learning for Predicting a Multi-regional Score Conveying the Degree of Lung Compromise in COVID-19 Patients. Institute of Electrical and Electronics Engineers (IEEE), 2022.
Harvard-tyylinen lähdeviittausAllahabadi, H., Amann, J., Balot, I., Beretta, A., Binkley, C., Bozenhard, J., . . . Sciences, A. U. o. A. 2022. Assessing Trustworthy AI in times of COVID-19. Deep Learning for predicting a multi-regional score conveying the degree of lung compromise in COVID-19 patients. Institute of Electrical and Electronics Engineers (IEEE).
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