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

We aimed to analyze the prognostic power of CT-based radiomics models using data of 14,339 COVID-19 patients. Whole lung segmentations were performed automatically using a deep learning-based model to extract 107 intensity and texture radiomics features. We used four feature selection algorithms and...

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Veröffentlicht in:	Computers in biology and medicine Jg. 145; S. 105467
Hauptverfasser:	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
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States Elsevier Ltd 01.06.2022 Elsevier Limited The Authors. Published by Elsevier Ltd
Schlagworte:	Algorithms Artificial intelligence Classifiers Coronaviruses COVID-19 COVID-19 - diagnostic imaging Datasets Deep learning Feature extraction Humans Internal Medicine Lung Neoplasms Lungs Machine Learning Medical prognosis Modelling Other Patients Polymerase chain reaction Prognosis Radiomics Retrospective Studies Sensitivity Statistical analysis Tomography, X-Ray Computed - methods Variance analysis X-ray CT COVID-19 X-ray CT Prognosis Machine learning Radiomics
ISSN:	0010-4825, 1879-0534, 1879-0534
Online-Zugang:	Volltext
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