Self-weighted Multi-task Learning for Subjective Cognitive Decline Diagnosis

Nina Cheng, Alejandro F Frangi, Zhi Guo Zhang, Denao Deng, Lihua Zhao, Tianfu Wang, Yichen Wei, Bihan Yu, Wei Mai, Gaoxiong Duan, Xiucheng Nong, Chong Li, Jiahui Su, Baiying Lei

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Subjective cognitive decline (SCD) is an early stage of mild cognitive impairment (MCI) and may represent the first symptom manifestation of Alzheimer’s disease (AD). Early diagnosis of MCI is important because early identification and intervention can delay or even reverse the progression of this disease. This paper proposes an automatic diagnostic framework for SCD and MCI. Specifically, we design a new multi-task learning model to integrate neuroimaging functional and structural connectivity in a predictive framework. We construct a functional brain network by sparse low-rank brain network estimation methods, and a structural brain network is constructed using fiber bundle tracking. Subsequently, we use multi-task learning methods to select features for integrated functional and structural connections, the importance of each task and the balance between both modalities are automatically learned. By integrating both functional and structural information, the most discriminative features of the disease are obtained for diagnosis. The experiments on the dataset show that our proposed method achieves good performance and is superior to the traditional algorithms. In addition, the proposed method can identify the most discriminative brain regions and connections. These results follow current clinical findings and add new findings for disease detection and future medical analysis.

Original languageEnglish
Title of host publicationMedical Image Computing and Computer Assisted Intervention – MICCAI 2020 - 23rd International Conference, Proceedings
EditorsAnne L. Martel, Purang Abolmaesumi, Danail Stoyanov, Diana Mateus, Maria A. Zuluaga, S. Kevin Zhou, Daniel Racoceanu, Leo Joskowicz
PublisherSpringer Nature
Pages104-113
Number of pages10
ISBN (Electronic)978-3-030-59728-3
ISBN (Print)978-3-030-59727-6
DOIs
Publication statusPublished - 4 Oct 2020
Event23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020 - Lima, Peru
Duration: 4 Oct 20208 Oct 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12267 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020
Country/TerritoryPeru
CityLima
Period4/10/208/10/20

Keywords

  • Feature selection
  • Multi-task learning
  • Subjective cognitive decline

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