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Diffusion tensor imaging-based machine learning for IDH wild-type glioblastoma stratification to reveal the biological underpinning of radiomic features.
Wang Z, Guan F, Duan W, Guo Y, Pei D, Qiu Y, Wang M, Xing A, Liu Z, Yu B, Zheng H, Liu X, Yan D, Ji Y, Cheng J, Yan J, Zhang Z. Wang Z, et al. Among authors: yan j, yan d. CNS Neurosci Ther. 2023 Nov;29(11):3339-3350. doi: 10.1111/cns.14263. Epub 2023 May 24. CNS Neurosci Ther. 2023. PMID: 37222229 Free PMC article.
Radiomic features from multiparametric magnetic resonance imaging predict molecular subgroups of pediatric low-grade gliomas.
Liu Z, Hong X, Wang L, Ma Z, Guan F, Wang W, Qiu Y, Zhang X, Duan W, Wang M, Sun C, Zhao Y, Duan J, Sun Q, Liu L, Ding L, Ji Y, Yan D, Liu X, Cheng J, Zhang Z, Li ZC, Yan J. Liu Z, et al. Among authors: yan j, yan d. BMC Cancer. 2023 Sep 11;23(1):848. doi: 10.1186/s12885-023-11338-8. BMC Cancer. 2023. PMID: 37697238 Free PMC article.
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.
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 ZC, Zhang Z. Yan J, et al. Lab Invest. 2022 Feb;102(2):154-159. doi: 10.1038/s41374-021-00692-5. Epub 2021 Nov 15. Lab Invest. 2022. PMID: 34782727 Free article.
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