Prediction of Parkinson's disease by transcranial sonography-based deep learning.

Journal: Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology
Published Date: Nov 20, 2023

Abstract

OBJECTIVES: Transcranial sonography has been used as a valid neuroimaging tool to diagnose Parkinson's disease (PD). This study aimed to develop a modified transcranial sonography (TCS) technique based on a deep convolutional neural network (DCNN) model to predict Parkinson's disease.

Authors

  • Chang Wei Ding
    School of Computer Science and Technology, China University of Mining and Technology, Xu'zhou 221000, China.
  • Ya Kun Ren
    Department of Ultrasound, The Second Affiliated Hospital of Soochow University, 1055 San Xiang Road, Suzhou, 215004, Jiangsu, China.
  • Cai Shan Wang
    Department of Ultrasound, The Second Affiliated Hospital of Soochow University, 1055 San Xiang Road, Suzhou, 215004, Jiangsu, China.
  • Ying Chun Zhang
    Department of Ultrasound, The Second Affiliated Hospital of Soochow University, 1055 San Xiang Road, Suzhou, 215004, Jiangsu, China. zyc1234@suda.edu.com.
  • Ying Zhang
    Department of Nephrology, Nanchong Central Hospital Affiliated to North Sichuan Medical College, Nanchong, China.
  • Min Yang
    College of Food Science and Engineering, Ocean University of China, Qingdao, 266003, Shandong, China.
  • Pan Mao
    Department of Ultrasound, The Second Affiliated Hospital of Soochow University, 1055 San Xiang Road, Suzhou, 215004, Jiangsu, China.
  • Yu Jing Sheng
    Department of Ultrasound, The Second Affiliated Hospital of Soochow University, 1055 San Xiang Road, Suzhou, 215004, Jiangsu, China.
  • Xiao Fang Chen
    Department of Ultrasound, The Second Affiliated Hospital of Soochow University, 1055 San Xiang Road, Suzhou, 215004, Jiangsu, China.
  • Chun Feng Liu
    Department of Neurology and Clinical Research Center of Neurological Disease, The Second Affiliated Hospital of Soochow University, Suzhou, 215004, China.

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