Radiomics-based machine learning model for efficiently classifying transcriptome subtypes in glioblastoma patients from MRI.

MLA

Le, Nguyen Quoc Khanh, et al. “Radiomics-Based Machine Learning Model for Efficiently Classifying Transcriptome Subtypes in Glioblastoma Patients from MRI.” Computers in Biology and Medicine, vol. 132, May 2021, p. 104320. EBSCOhost, https://doi.org/10.1016/j.compbiomed.2021.104320.

APA

Le, N. Q. K., Hung, T. N. K., Do, D. T., Lam, L. H. T., Dang, L. H., & Huynh, T.-T. (2021). Radiomics-based machine learning model for efficiently classifying transcriptome subtypes in glioblastoma patients from MRI. Computers in Biology and Medicine, 132, 104320. https://doi.org/10.1016/j.compbiomed.2021.104320

Chicago

Le, Nguyen Quoc Khanh, Truong Nguyen Khanh Hung, Duyen Thi Do, Luu Ho Thanh Lam, Luong Huu Dang, and Tuan-Tu Huynh. 2021. “Radiomics-Based Machine Learning Model for Efficiently Classifying Transcriptome Subtypes in Glioblastoma Patients from MRI.” Computers in Biology and Medicine 132 (May): 104320. doi:10.1016/j.compbiomed.2021.104320.