skip to main content
10.1145/2649387.2660797acmconferencesArticle/Chapter ViewAbstractPublication PagesbcbConference Proceedingsconference-collections
poster

A structured approach to ensemble learning for Alzheimer's disease prediction

Published:20 September 2014Publication History

ABSTRACT

This research employs an exhaustive search of different attribute selection algorithms in order to provide a more structured approach to learning design for prediction of Alzheimer's clinical dementia rating (CDR).

References

  1. A. Association et al. Alzheimer's disease fact sheet. Alzheimer's Association, 2011.Google ScholarGoogle Scholar
  2. D. G. Flood, G. J. Marek, and M. Williams. Developing predictive csf biomarkers?a challenge critical to success in alzheimer's disease and neuropsychiatric translational medicine. Biochemical pharmacology, 81(12):1422--1434, 2011.Google ScholarGoogle ScholarCross RefCross Ref
  3. L. C. Lu and J. H. Bludau. Alzheimer's Disease. Greenwood Publishing Group, 2011.Google ScholarGoogle Scholar
  4. J. Lundkvist, M. M. Halldin, J. Sandin, G. Nordvall, P. Forsell, S. Svensson, L. Jansson, G. Johansson, B. Winblad, and J. Ekstrand. The battle of alzheimer?s disease--the beginning of the future unleashing the potential of academic discoveries. Frontiers in pharmacology, 5, 2014.Google ScholarGoogle Scholar
  5. J. C. Morris. The clinical dementia rating (cdr): current version and scoring rules. Neurology, 1993.Google ScholarGoogle Scholar

Index Terms

  1. A structured approach to ensemble learning for Alzheimer's disease prediction

    Recommendations

    Comments

    Login options

    Check if you have access through your login credentials or your institution to get full access on this article.

    Sign in
    • Published in

      cover image ACM Conferences
      BCB '14: Proceedings of the 5th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics
      September 2014
      851 pages
      ISBN:9781450328944
      DOI:10.1145/2649387
      • General Chairs:
      • Pierre Baldi,
      • Wei Wang

      Copyright © 2014 Owner/Author

      Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 20 September 2014

      Check for updates

      Qualifiers

      • poster

      Acceptance Rates

      Overall Acceptance Rate254of885submissions,29%

    PDF Format

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader