COVID-19 prognostic modeling using CT radiomic features and machine learning algorithms: Analysis of a multi-institutional dataset of 14,339 patients-Reference-Cited by-同舟云学术

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

Published:2022-06 Issue: Volume:145 Page:105467
ISSN:0010-4825
Container-title:Computers in Biology and Medicine
language:en
Short-container-title:Computers in Biology and Medicine

Author:

Shiri Isaac,Salimi Yazdan,Pakbin Masoumeh,Hajianfar Ghasem,Avval Atlas Haddadi,Sanaat Amirhossein,Mostafaei Shayan,Akhavanallaf Azadeh,Saberi Abdollah,Mansouri Zahra,Askari Dariush,Ghasemian Mohammadreza,Sharifipour Ehsan,Sandoughdaran Saleh,Sohrabi Ahmad,Sadati Elham,Livani Somayeh,Iranpour Pooya,Kolahi Shahriar,Khateri Maziar,Bijari Salar,Atashzar Mohammad Reza,Shayesteh Sajad P.,Khosravi Bardia,Babaei Mohammad Reza,Jenabi Elnaz,Hasanian Mohammad,Shahhamzeh Alireza,Foroghi Ghomi Seyaed Yaser,Mozafari Abolfazl,Teimouri Arash,Movaseghi Fatemeh,Ahmari Azin,Goharpey Neda,Bozorgmehr Rama,Shirzad-Aski Hesamaddin,Mortazavi Roozbeh,Karimi Jalal,Mortazavi Nazanin,Besharat Sima,Afsharpad Mandana,Abdollahi Hamid,Geramifar Parham,Radmard Amir Reza,Arabi Hossein,Rezaei-Kalantari Kiara,Oveisi Mehrdad,Rahmim Arman,Zaidi Habib^ORCID

Funder

Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung

Publisher

Elsevier BV

Subject

Health Informatics,Computer Science Applications

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