A Multi-Label Deep Learning Model for Detailed Classification of Alzheimer's Disease.

Journal: Actas espanolas de psiquiatria
Published Date: Jan 1, 2025

Abstract

BACKGROUND: Accurate diagnosis and classification of Alzheimer's disease (AD) are crucial for effective treatment and management. Traditional diagnostic models, largely based on binary classification systems, fail to adequately capture the complexities and variations across different stages and subtypes of AD, limiting their clinical utility.

Authors

  • Mei Yang
    Department of Geriatric Cardiology; National Center for Clinical Research of Geriatric Diseases, Xiangya Hospital, Central South University, Changsha 410008, China.
  • Yuanzhi Zhao
    Department of Psychiatry, Affiliated Kangning Hospital of Ningbo University, 315201 Ningbo, Zhejiang, China; Department of Psychiatry, Ningbo Kangning Hospital, 315201 Ningbo, Zhejiang, China.
  • Haihang Yu
    Department of Psychiatry, Affiliated Kangning Hospital of Ningbo University, 315201 Ningbo, Zhejiang, China; Department of Psychiatry, Ningbo Kangning Hospital, 315201 Ningbo, Zhejiang, China.
  • Shoulin Chen
    Department of Psychiatry, Affiliated Kangning Hospital of Ningbo University, 315201 Ningbo, Zhejiang, China; Department of Psychiatry, Ningbo Kangning Hospital, 315201 Ningbo, Zhejiang, China.
  • Guosheng Gao
    Department of Clinical Laboratory, Ningbo No.2 Hospital, Ningbo, Zhejiang, China.
  • Da Li
  • Xiangping Wu
    Department of Psychiatry, Affiliated Kangning Hospital of Ningbo University, 315201 Ningbo, Zhejiang, China; Department of Psychiatry, Ningbo Kangning Hospital, 315201 Ningbo, Zhejiang, China.
  • Ling Huang
    School of Civil Engineering and Transportation, South China University of Technology, Guangzhou, 510640, China.
  • Shuyuan Ye
    Department of Clinical Laboratory, Ningbo No.2 Hospital, 315099 Ningbo, Zhejiang, China.

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