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Computed tomography-based radiomics machine learning classifiers to differentiate type I and type II epithelial ovarian cancers.
Li, Jiaojiao; Li, Xubin; Ma, Juanwei; Wang, Fang; Cui, Shujun; Ye, Zhaoxiang.
  • Li J; Department of Radiology, First Affiliated Hospital of Hebei North University, No. 12, Changqing Road, Qiaoxi District, Zhangjiakou, 075000, China.
  • Li X; Department of Radiology, National Clinical Research Center for Cancer, Tianjin Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Huanhuxi Road, Hexi District, Tianjin, 300060, China.
  • Ma J; Department of Radiology, National Clinical Research Center for Cancer, Tianjin Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Huanhuxi Road, Hexi District, Tianjin, 300060, China.
  • Wang F; Department of Radiology, National Clinical Research Center for Cancer, Tianjin Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Huanhuxi Road, Hexi District, Tianjin, 300060, China.
  • Cui S; Department of Radiology, National Clinical Research Center for Cancer, Tianjin Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Huanhuxi Road, Hexi District, Tianjin, 300060, China.
  • Ye Z; Department of Radiology, First Affiliated Hospital of Hebei North University, No. 12, Changqing Road, Qiaoxi District, Zhangjiakou, 075000, China. hbzjkcsj@126.com.
Eur Radiol ; 33(7): 5193-5204, 2023 Jul.
Article en En | MEDLINE | ID: mdl-36515713
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Neoplasias Ováricas / Tomografía Computarizada por Rayos X Tipo de estudio: Prognostic_studies Límite: Female / Humans Idioma: En Año: 2023 Tipo del documento: Article
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Neoplasias Ováricas / Tomografía Computarizada por Rayos X Tipo de estudio: Prognostic_studies Límite: Female / Humans Idioma: En Año: 2023 Tipo del documento: Article