首页> Neuro-oncology> Automated machine learning based on radiomics features predicts H3 K27M mutation in midline gliomas of the brain.

Automated machine learning based on radiomics features predicts H3 K27M mutation in midline gliomas of the brain.

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第一作者： Xiaorui,Su

第一单位： Huaxi MR Research Center, Department of Radiology, West China Hospital of Sichuan University, Chengdu, China.;Huaxi Glioma Center, West China Hospital of Sichuan University, Chengdu, China.

作者： Xiaorui,Su ^[1] ; Ni,Chen ^[2] ; Huaiqiang,Sun ^[3] ; Yanhui,Liu ^[4] ; Xibiao,Yang ^[5] ; Weina,Wang ^[3] ; Simin,Zhang ^[3] ; Qiaoyue,Tan ^[3] ; Jingkai,Su ^[3] ; Qiyong,Gong ^[3] ; Qiang,Yue ^[6]

作者单位： Huaxi MR Research Center, Department of Radiology, West China Hospital of Sichuan University, Chengdu, China.;Huaxi Glioma Center, West China Hospital of Sichuan University, Chengdu, China. ^[1] Department of Pathology, West China Hospital of Sichuan University, Chengdu, China.;Huaxi Glioma Center, West China Hospital of Sichuan University, Chengdu, China. ^[2] Huaxi MR Research Center, Department of Radiology, West China Hospital of Sichuan University, Chengdu, China. ^[3] Department of Neurosurgery, West China Hospital of Sichuan University, Chengdu, China.;Huaxi Glioma Center, West China Hospital of Sichuan University, Chengdu, China. ^[4] Department of Radiology, West China Hospital of Sichuan University, Chengdu, China. ^[5] Department of Radiology, West China Hospital of Sichuan University, Chengdu, China.;Huaxi Glioma Center, West China Hospital of Sichuan University, Chengdu, China. ^[6]

关键词 H3 K27M mutation automated machine learning TPOT Tree-based Pipeline Optimization Tool autoML midline glioma