Machine Learning-based Overall Survival Prediction in GBM Patients Using MRI Radiomics-Reference-Cited by-同舟云学术

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Machine Learning-based Overall Survival Prediction in GBM Patients Using MRI Radiomics

Published:2022-11-05 Issue: Volume: Page:1-3
ISSN:
Container-title:2022 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC)
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Author:

Hajianfar Ghasem¹,Avval Atlas Haddadi²,Ali Hosseini Seyyed³,Oveisi Mehrdad⁴,Shiri Isaac⁵,Zaidi Habib⁵

Affiliation:

1. Iran University of Medical Sciences,Rajaie Cardiovascular Medical and Research Center,Tehran,Iran

2. Mashhad University of Medical Sciences,School of Medicine,Mashhad,Iran

3. Tehran University of Medical Sciences,Department of Medical Physics and Biomedical Engineering,Tehran,Iran

4. King’s College London,Comprehensive Cancer Centre, School of Cancer & Pharmaceutical Sciences, Faculty of Life Sciences & Medicine,London,United Kingdom

5. Geneva University Hospital,Division of Nuclear Medicine and Molecular Imaging,Geneva 4,Switzerland,1211

Funder

National Science Foundation

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10398888/10398889/10398971.pdf?arnumber=10398971

Reference18 articles.

1. Epidemiology and Outcome of Glioblastoma

2. Understanding and Treating Glioblastoma

3. Tensor Radiomics: Paradigm for Systematic Incorporation of Multi-Flavoured Radiomics Features

4. Synergistic impact of motion and acquisition/reconstruction parameters on ¹⁸ F‐FDG PET radiomic features in non‐small cell lung cancer: Phantom and clinical studies

5. Impact of feature harmonization on radiogenomics analysis: Prediction of EGFR and KRAS mutations from non-small cell lung cancer PET/CT images

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