Dynamic 3D radiomics analysis using artificial intelligence to assess the stage of COVID-19 on CT images

[1] Fang Y(2020)Sensitivity of chest CT for COVID-19: comparison to RT-PCR Radiology 296 E115-E117

[2] Zhang H(2020)The first case of 2019 novel coronavirus pneumonia imported into Korea from Wuhan, China: implication for infection prevention and control measures J Korean Med Sci 35 e61-721

[3] Xie J(2020)CT radiomics can help screen the coronavirus disease 2019 (COVID-19): a preliminary study Sci China Inf Sci 295 715-331

[4] Kim JY(2020)Time course of lung changes at chest CT during recovery from coronavirus disease 2019 (COVID-19) Radiology 181 e1411-165

[5] Choe PG(2020)Clinically applicable AI system for accurate diagnosis, quantitative measurements, and prognosis of COVID-19 pneumonia using computed tomography Cell 36 321-1547

[6] Oh Y(2020)Guideline for medical imaging in auxiliary diagnosis of coronavirus disease 2019 Chin J Med Imaging Technol 5 4006-1914

[7] Fang M(2014)Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach Nat Commun 11 153-6

[8] He B(2018)Applications of random forest feature selection for fine-scale genetic population assignment Evol Appl 33 1532-E008

[9] Li L(2010)Feature selection and kernel learning for local learning-based clustering IEEE Trans Pattern Anal Mach Intell 92 1902-838

[10] Pan F(2020)Clinical characteristics of 3062 COVID-19 patients: a meta-analysis J Med Virol 12 11245-389

[1] Fang Y(2020)Sensitivity of chest CT for COVID-19: comparison to RT-PCR Radiology 296 E115-E117

[2] Zhang H(2020)The first case of 2019 novel coronavirus pneumonia imported into Korea from Wuhan, China: implication for infection prevention and control measures J Korean Med Sci 35 e61-721

[3] Xie J(2020)CT radiomics can help screen the coronavirus disease 2019 (COVID-19): a preliminary study Sci China Inf Sci 295 715-331

[4] Kim JY(2020)Time course of lung changes at chest CT during recovery from coronavirus disease 2019 (COVID-19) Radiology 181 e1411-165

[5] Choe PG(2020)Clinically applicable AI system for accurate diagnosis, quantitative measurements, and prognosis of COVID-19 pneumonia using computed tomography Cell 36 321-1547

[6] Oh Y(2020)Guideline for medical imaging in auxiliary diagnosis of coronavirus disease 2019 Chin J Med Imaging Technol 5 4006-1914

[7] Fang M(2014)Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach Nat Commun 11 153-6

[8] He B(2018)Applications of random forest feature selection for fine-scale genetic population assignment Evol Appl 33 1532-E008

[9] Li L(2010)Feature selection and kernel learning for local learning-based clustering IEEE Trans Pattern Anal Mach Intell 92 1902-838

[10] Pan F(2020)Clinical characteristics of 3062 COVID-19 patients: a meta-analysis J Med Virol 12 11245-389