Contralateral artery enlargement predicts carotid plaque progression based on machine learning algorithm models in apoE mice.

Journal: Biomedical engineering online
Published Date: Dec 28, 2016

Abstract

BACKGROUND: This study specifically focused on anatomical MRI characterization of the low shear stress-induced atherosclerotic plaque in mice. We used machine learning algorithms to analyze multiple correlation factors of plaque to generate predictive models and to find the predictive factor for vulnerable plaque.

Authors

  • Bing Li
  • Yun Jiao
    Jiangsu Key Lab of Molecular and Function Imaging, Department of Radiology, Zhongda Hospital, Medical School of Southeast University, Nanjing, 210009, China.
  • Cong Fu
    Department of Cardiology, Zhongda Hospital, Medical School of Southeast University, 87 Dingjiaqiao, Nanjing, 210009, Jiangsu, China.
  • Bo Xie
    Department of Orthodontics, The Affiliated Stomatological Hospital of Southwest Medical University, Luzhou, China.
  • Genshan Ma
    Department of Cardiology, Zhongda Hospital, Medical School of Southeast University, 87 Dingjiaqiao, Nanjing, 210009, Jiangsu, China.
  • Gaojun Teng
    Jiangsu Key Lab of Molecular and Function Imaging, Department of Radiology, Zhongda Hospital, Medical School of Southeast University, Nanjing, 210009, China.
  • Yuyu Yao
    Department of Cardiology, Zhongda Hospital, Medical School of Southeast University, 87 Dingjiaqiao, Nanjing, 210009, Jiangsu, China. yaoyuyunj@hotmail.com.

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