Predicting 1p/19q co-deletion status from magnetic resonance imaging using deep learning in adult-type diffuse lower-grade gliomas: a discovery and validation study.

MLA

Yan, Jing, et al. “Predicting 1p/19q Co-Deletion Status from Magnetic Resonance Imaging Using Deep Learning in Adult-Type Diffuse Lower-Grade Gliomas: A Discovery and Validation Study.” Laboratory Investigation; a Journal of Technical Methods and Pathology, vol. 102, no. 2, Feb. 2022, pp. 154–59. EBSCOhost, https://doi.org/10.1038/s41374-021-00692-5.

APA

Yan, J., Zhang, S., Sun, Q., Wang, W., Duan, W., Wang, L., Ding, T., Pei, D., Sun, C., Wang, W., Liu, Z., Hong, X., Wang, X., Guo, Y., Li, W., Cheng, J., Liu, X., Li, Z.-C., & Zhang, Z. (2022). Predicting 1p/19q co-deletion status from magnetic resonance imaging using deep learning in adult-type diffuse lower-grade gliomas: a discovery and validation study. Laboratory Investigation; a Journal of Technical Methods and Pathology, 102(2), 154–159. https://doi.org/10.1038/s41374-021-00692-5

Chicago

Yan, Jing, Shenghai Zhang, Qiuchang Sun, Weiwei Wang, Wenchao Duan, Li Wang, Tianqing Ding, et al. 2022. “Predicting 1p/19q Co-Deletion Status from Magnetic Resonance Imaging Using Deep Learning in Adult-Type Diffuse Lower-Grade Gliomas: A Discovery and Validation Study.” Laboratory Investigation; a Journal of Technical Methods and Pathology 102 (2): 154–59. doi:10.1038/s41374-021-00692-5.