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Radiomics and machine learning may accurately predict the grade and histological subtype in meningiomas using conventional and diffusion tensor imaging.

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第一作者： Yae Won,Park

第一单位： Department of Radiology, Ewha Womans University College of Medicine, Seoul, South Korea.;Department of Radiology and Research Institute of Radiological Science, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 120-752, South Korea.

作者： Yae Won,Park ^[1] ; Jongmin,Oh ^[2] ; Seng Chan,You ^[3] ; Kyunghwa,Han ^[4] ; Sung Soo,Ahn ^[5] ; Yoon Seong,Choi ^[4] ; Jong Hee,Chang ^[6] ; Se Hoon,Kim ^[7] ; Seung-Koo,Lee ^[4]

作者单位： Department of Radiology, Ewha Womans University College of Medicine, Seoul, South Korea.;Department of Radiology and Research Institute of Radiological Science, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 120-752, South Korea. ^[1] Department of Convergence Medicine, Ewha Womans University College of Medicine, Seoul, South Korea. ^[2] Department of Biomedical Informatics, Ajou University School of Medicine, Suwon, South Korea. ^[3] Department of Radiology and Research Institute of Radiological Science, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 120-752, South Korea. ^[4] Department of Radiology and Research Institute of Radiological Science, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 120-752, South Korea. sungsoo@yuhs.ac. ^[5] Department of Neurosurgery, Yonsei University College of Medicine, Seoul, South Korea. ^[6] Department of Pathology, Yonsei University College of Medicine, Seoul, South Korea. ^[7]

关键词 Diffusion tensor imaging Magnetic resonance imaging Meningioma Radiomics