CP and pneumonia: In addition, the model proposed by Jin et al.[30], developed on a dataset of 9025 subjects, which is an amalgamation of their own data and several other public datasets (e.g. LIDC–IDRI [31], Tianchi-Alibaba [32], MosMedData [33], and CC-CCII), gained an accuracy of 0.975 for diagnosing between COVID-19 and three other classes (non-pneumonia, non-viral community-acquired pneumonia, Influenza-A/B), 0.921 for between COVID-19 and the CP and Normal classes on the CC-CCII dataset, and 0.933 for between COVID-19 from non-pneumonia on the MosMedData cohort.