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AJNR Awards, New Junior Editors, and more. Read the latest AJNR updates

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Index by author

January 01, 2020; Volume 41,Issue 1
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  1. Qin, L.

    1. FELLOWS' JOURNAL CLUBAdult Brain
      Open Access
      Deep Transfer Learning and Radiomics Feature Prediction of Survival of Patients with High-Grade Gliomas
      W. Han, L. Qin, C. Bay, X. Chen, K.-H. Yu, N. Miskin, A. Li, X. Xu and G. Young
      American Journal of Neuroradiology January 2020, 41 (1) 40-48; DOI: https://doi.org/10.3174/ajnr.A6365

      Fifty patients with high-grade gliomas from the authors’ hospital and 128 patients with high-grade gliomas from The Cancer Genome Atlas were included in this study. For each patient, the authors calculated 348 hand-crafted radiomics features and 8192 deep features generated by a pretrained convolutional neural network. They then applied feature selection and Elastic Net-Cox modeling to differentiate patients into long- and short-term survivors. In the 50 patients with high-grade gliomas from their institution, the combined feature analysis framework classified the patients into long- and short-term survivor groups with a log-rank test P value <.001. In the 128 patients from The Cancer Genome Atlas, the framework classified patients into long- and short-term survivors with a log-rank test P value of .014. In conclusion, the authors report successful production and initial validation of a deep transfer learning model combining radiomics and deep features to predict overall survival of patients with glioblastoma from postcontrast T1-weighed brain MR imaging.

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American Journal of Neuroradiology: 41 (1)
American Journal of Neuroradiology
Vol. 41, Issue 1
1 Jan 2020
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