Prediction of rupture risk in anterior communicating artery aneurysms with a feed-forward artificial neural network.

Journal: European radiology
Published Date: Aug 1, 2018

Abstract

OBJECTIVES: Anterior communicating artery (ACOM) aneurysms are the most common intracranial aneurysms, and predicting their rupture risk is challenging. We aimed to predict this risk using a two-layer feed-forward artificial neural network (ANN).

Authors

  • Jinjin Liu
    School of Public Health, Hengyang Medical School, University of South China, Hengyang 421001, P. R. China.
  • Yongchun Chen
    Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, 325000, China.
  • Li Lan
    Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, 325000, China.
  • Boli Lin
    Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, 325000, China.
  • Weijian Chen
    Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, 325000, China.
  • Meihao Wang
    Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, PR China.
  • Rui Li
    Department of Oncology, Xiyuan Hospital, China Academy of Chinese Medical Science, Beijing, China.
  • Yunjun Yang
    Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, 325000, China. yyjunjim@163.com.
  • Bing Zhao
    Department of Neurology, Changzhi People's Hospital, Changzhi Medical College, Changzhi, China.
  • Zilong Hu
    Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, 325000, China.
  • Yuxia Duan
    Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, 325000, China.

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