Display Settings:

Format

Send to:

Choose Destination
See comment in PubMed Commons below
J Alzheimers Dis. 2012;32(4):997-1010. doi: 10.3233/JAD-2012-121024.

Bioprofile analysis: a new approach for the analysis of biomedical data in Alzheimer's disease.

Author information

  • 1Signal Processing and Multimedia Communications Research Group, School of Computing and Mathematics, Plymouth University, Plymouth, UK. javier.escudero@ieee.org

Abstract

This article presents a new approach for the analysis of biomedical data to support the management and care of patients with Alzheimer's disease (AD). The increase in prevalence of neurodegenerative disorders such as AD has led to a need for objective means to assist clinicians with the analysis and interpretation of complex biomedical data. To this end, we propose a "Bioprofile" analysis to reveal the pattern of disease in the subject's biodata. From the Bioprofile, personal "Bioindices" that indicate how closely a subject's data resemble the pattern of AD can be derived. We used an unsupervised technique (k-means) to cluster variables of the ADNI database so that subjects are divisible into those with the Bioprofile of AD and those without it. Results revealed that there is an "AD pattern" in the biodata of most AD and mild cognitive impairment (MCI) patients and some controls. This pattern agrees with a recent hypothetical model of AD evolution. We also assessed how the Bioindices changed with time and we found that the Bioprofile was associated with the risk of progressing from MCI to AD. Hence, the Bioprofile analysis is a promising methodology that may potentially provide a complementary new way of interpreting biomedical data. Furthermore, the concept of the Bioprofile could be extended to other neurodegenerative diseases.

PMID:
22886027
[PubMed - indexed for MEDLINE]
PubMed Commons home

PubMed Commons

0 comments
How to join PubMed Commons

    Supplemental Content

    Icon for IOS Press
    Loading ...
    Write to the Help Desk