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

Isaac Shiri, Yazdan Salimi, Masoumeh Pakbin, Ghasem Hajianfar, Atlas Haddadi Avval, Amirhossein Sanaat, Shayan Mostafaei, Azadeh Akhavanallaf, Abdollah Saberi, Zahra Mansouri, Dariush Askari, Mohammadreza Ghasemian, Ehsan Sharifipour, Saleh Sandoughdaran, Ahmad Sohrabi, Elham Sadati, Somayeh Livani, Pooya Iranpour, Shahriar Kolahi, Maziar Khateri, Salar Bijari, Mohammad Reza Atashzar, Sajad P. Shayesteh, Bardia Khosravi, Mohammadreza Babaei, Elnaz Jenabi, Mohammad Hasanian, Alireza Shahhamzeh, Seyaed Yaser Foroghi Ghomi, Abolfazl Mozafari, Arash Teimouri, Fatemeh Movaseghi, Azin Ahmari, Neda Goharpey, Rama Bozorgmehr, Hesamaddin Shirzad-Aski, Roozbeh Mortazavi, Jalal Karimi, Nazanin Mortazavi, Sima Besharat, Mandana Afsharpad, Hamid Abdollahi, Parham Geramifar, Amir Reza Radmard, Hossein Arabi, Kiara Rezaei-Kalantari, Mehrdad Oveisi, Arman Rahmim, Habib Zaidi. COVID-19 prognostic modeling using CT radiomic features and machine learning algorithms: Analysis of a multi-institutional dataset of 14, 339 patients. Comp. in Bio. and Med., 145:105467, 2022. [doi]

Abstract

Abstract is missing.