COVID-19 prognostic modeling using CT radiomic features and machine learning algorithms: Analysis of a multi-institutional dataset of 14,339 patients

التفاصيل البيبلوغرافية
العنوان:	COVID-19 prognostic modeling using CT radiomic features and machine learning algorithms: Analysis of a multi-institutional dataset of 14,339 patients
المؤلفون:	Shiri, I, Salimi, Y, Pakbin, M, Hajianfar, G, Avval, AH, Sanaat, A, Mostafaei, S, Akhavanallaf, A, Saberi, A, Mansouri, Z, Askari, D, Ghasemian, M, Sharifipour, E, Sandoughdaran, S, Sohrabi, A, Sadati, E, Livani, S, Iranpour, P, Kolahi, S, Khateri, M, Bijari, S, Atashzar, MR, Shayesteh, SP, Khosravi, B, Babaei, MR, Jenabi, E, Hasanian, M, Shahhamzeh, A, Ghomi, SYF, Mozafari, A, Teimouri, A, Movaseghi, F, Ahmari, A, Goharpey, N, Bozorgmehr, R, Shirzad-Aski, H, Mortazavi, R, Karimi, J, Mortazavi, N, Besharat, S, Afsharpad, M, Abdollahi, H, Geramifar, P, Radmard, AR, Arabi, H, Rezaei-Kalantari, K, Oveisi, M, Rahmim, A, Zaidi, H
المصدر:	Computers in biology and medicine. 145:105467
مصطلحات موضوعية:	Medicin och hälsovetenskap
URL الوصول:	http://kipublications.ki.se/Default.aspx?queryparsed=id:154655386
قاعدة البيانات:	SwePub

الوصف
تدمد:	18790534
DOI:	10.1016/j.compbiomed.2022.105467