Radiomics Features Predict Telomerase Reverse Transcriptase Promoter Mutations in World Health Organization Grade II Gliomas via a Machine-Learning Approach

The detection of mutations in telomerase reverse transcriptase promoter (pTERT) is important since preoperative diagnosis of pTERT status helps with evaluating prognosis and determining the surgical strategy. Here, we aimed to establish a radiomics-based machine-learning algorithm and evaluated its...

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Tallennettuna:
Bibliografiset tiedot
Julkaisussa:Front Oncol
Päätekijät: Fang, Shengyu, Fan, Ziwen, Sun, Zhiyan, Li, Yiming, Liu, Xing, Liang, Yuchao, Liu, Yukun, Zhou, Chunyao, Zhu, Qiang, Zhang, Hong, Li, Tianshi, Li, Shaowu, Jiang, Tao, Wang, Yinyan, Wang, Lei
Aineistotyyppi: Artigo
Kieli:Inglês
Julkaistu: Frontiers Media S.A. 2021
Aiheet:
Oncology
Linkit:https://ncbi.nlm.nih.gov/pmc/articles/PMC7905226/
https://ncbi.nlm.nih.gov/pubmed/33643908
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fonc.2020.606741
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