Survival Prediction in Glioblastoma Using Combination of Deep Learning and Hand-Crafted Radiomic Features in MRI Images-Reference-Cited by-同舟云学术

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Survival Prediction in Glioblastoma Using Combination of Deep Learning and Hand-Crafted Radiomic Features in MRI Images

Published:2023 Issue:6 Volume:14 Page:1461-1469
ISSN:1798-2340
Container-title:Journal of Advances in Information Technology
language:
Short-container-title:JAIT

Author:

Zhuge Ying,Ning Holly,Cheng Jason Y.,Tasci Erdal,Mathen Peter,Camphausen Kevin,Miller Robert W.,Krauze Andra V.

Publisher

Engineering and Technology Publishing

Link

https://www.jait.us/uploadfile/2023/JAIT-V14N6-1461.pdf

Reference52 articles.

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2. [2] E. G. V. Meir, C. G. Hadjipanayis, A. D. Norden, H. K. Shu, P. Y. Wen, and J. J. Olson, "Exciting new advances in neuro-oncology: The avenue to a cure for malignant glioma," CA Cancer J. Clin., vol. 60, no. 3, pp. 166193, 2010.

3. [3] R. A. Morshed, J. S. Young, S. L. Hervey-Jumper, and M. S. Berger, "The management of low-grade gliomas in adults," J. Neurosurg Sci., vol. 63, no. 4, pp. 450457, Aug. 2019.

4. [4] M. Geurts and M. J. V. D. Bent, "On high-risk, low-grade glioma: What distinguishes high from low?" Cancer, vol. 125, no. 2, pp. 174176, 2019.

5. [5] M. J. V. D. Bent, M. Smits, J. M. Kros, and S. M. Chang, "Diffuse infiltrating oligodendroglioma and astrocytoma," J. Clin. Oncol., vol. 35, no. 21, pp. 23942401, 2017.

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