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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

Crossref DOI link: https://doi.org/10.1038/s41374-021-00692-5

Published Print: 2022-02

Update policy: https://doi.org/10.1016/elsevier_cm_policy

Authors

Yan, Jing

Zhang, Shenghai

Sun, Qiuchang

Wang, Weiwei

Duan, Wenchao

Wang, Li

Ding, Tianqing

Pei, Dongling

Sun, Chen

Wang, Wenqing

Liu, Zhen

Hong, Xuanke

Wang, Xiangxiang

Guo, Yu

Li, Wencai

Cheng, Jingliang

Liu, Xianzhi

Li, Zhi-Cheng

Zhang, Zhenyu https://orcid.org/0000-0001-5570-090X
Funding

Funding for this research was provided by:

National Natural Science Foundation of China (81702465)
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Text and Data Mining valid from 2022-02-01

Text and Data Mining valid from 2022-02-01

Version of Record valid from 2023-02-01
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This article is maintained by: Elsevier

Article Title: 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

Journal Title: Laboratory Investigation

CrossRef DOI link to publisher maintained version: https://doi.org/10.1038/s41374-021-00692-5

Content Type: article

Copyright: © 2021 United States & Canadian Academy of Pathology.

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