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A pilot study using a machine-learning approach of morphological and hemodynamic parameters for predicting aneurysms enhancement.
Lv, Nan; Karmonik, Christof; Shi, Zhaoyue; Chen, Shiyue; Wang, Xinrui; Liu, Jianmin; Huang, Qinghai.
Afiliação
  • Lv N; Department of Neurosurgery, Changhai Hospital, Second Military Medical University, Shanghai, China.
  • Karmonik C; Translational Imaging Center, Houston Methodist Research Institute, Houston, TX, USA. ckarmonik@houstonmethodist.org.
  • Shi Z; Translational Imaging Center, Houston Methodist Research Institute, Houston, TX, USA.
  • Chen S; Department of Radiology, Changhai Hospital, Second Military Medical University, Shanghai, China.
  • Wang X; Department of Radiology, Changhai Hospital, Second Military Medical University, Shanghai, China.
  • Liu J; Department of Neurosurgery, Changhai Hospital, Second Military Medical University, Shanghai, China.
  • Huang Q; Department of Neurosurgery, Changhai Hospital, Second Military Medical University, Shanghai, China.
Int J Comput Assist Radiol Surg ; 15(8): 1313-1321, 2020 Aug.
Article em En | MEDLINE | ID: mdl-32514728
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Aneurisma Intracraniano / Aneurisma Roto / Aprendizado de Máquina / Hemodinâmica Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Female / Humans / Male / Middle aged Idioma: En Ano de publicação: 2020 Tipo de documento: Article
Texto completo
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XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Aneurisma Intracraniano / Aneurisma Roto / Aprendizado de Máquina / Hemodinâmica Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Female / Humans / Male / Middle aged Idioma: En Ano de publicação: 2020 Tipo de documento: Article