Evaluation and Prediction of Early Alzheimer's Disease Using a Machine Learning-based Optimized Combination-Feature Set on Gray Matter Volume and Quantitative Susceptibility Mapping.

Journal: Current Alzheimer research
Published Date: Jan 1, 2020

Abstract

BACKGROUND: Because Alzheimer's Disease (AD) has very complicated pattern changes, it is difficult to evaluate it with a specific factor. Recently, novel machine learning methods have been applied to solve limitations.

Authors

  • Hyug-Gi Kim
    Department of Biomedical Engineering, Graduate School, Kyung Hee University, 1732, Deogyeong-daero, Giheunggu, Yongin-si, Gyeonggi-do 446-701, Korea.
  • Soonchan Park
    Department of Radiology, Kyung Hee University Hospital at Gangdong, College of Medicine, Kyung Hee University 892 Dongnam-ro, Gangdong-Gu, Seoul-05278, Korea.
  • Hak Y Rhee
    Department of Neurology, Kyung Hee University, Hospital at Gangdong, College of Medicine, Kyung Hee University 892 Dongnam-ro, Gangdong-Gu, Seoul-05278, Korea.
  • Kyung M Lee
    Department of Radiology, Kyung Hee University Hospital, College of Medicine, Kyung Hee University 23, Kyung Hee Dae-ro, Dongdaemun-gu, Seoul-130-872, Korea.
  • Chang-Woo Ryu
    Department of Radiology, Kyung Hee University Hospital at Gangdong, College of Medicine, Kyung Hee University 892 Dongnam-ro, Gangdong-Gu, Seoul-05278, Korea.
  • Soo Y Lee
    Department of Biomedical Engineering, Graduate School, Kyung Hee University, 1732, Deogyeong-daero, Giheunggu, Yongin-si, Gyeonggi-do 446-701, Korea.
  • Eui J Kim
    Department of Radiology, Kyung Hee University Hospital, College of Medicine, Kyung Hee University 23, Kyung Hee Dae-ro, Dongdaemun-gu, Seoul-130-872, Korea.
  • Yi Wang
    Department of Neurology, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai, China.
  • Geon-Ho Jahng
    Department of Radiology, Kyung Hee University Hospital at Gangdong, College of Medicine, Kyung Hee University 892 Dongnam-ro, Gangdong-Gu, Seoul-05278, Korea.

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