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

Sat, 01 Jan 2022 00:00:00 +0100

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, Seyed 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. Comput. Biol. Medicine 145: 105467 (2022)