Journal article
Comparative multiresolution wavelet analysis of ERP spectral bands using an ensemble of classifiers approach for early diagnosis of Alzheimer's disease
Computers in biology and medicine, v 37(4), pp 542-558
2007
PMID: 16989799
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Early diagnosis of Alzheimer's disease (AD) is becoming an increasingly important healthcare concern. Prior approaches analyzing event-related potentials (ERPs) had varying degrees of success, primarily due to smaller study cohorts, and the inherent difficulty of the problem. A new effort using multiresolution analysis of ERPs is described. Distinctions of this study include analyzing a larger cohort, comparing different wavelets and different frequency bands, using ensemble-based decisions and, most importantly, aiming the earliest possible diagnosis of the disease. Surprising yet promising outcomes indicate that ERPs in response to novel sounds of oddball paradigm may be more reliable as a biomarker than the more commonly used responses to target sounds.
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Details
- Title
- Comparative multiresolution wavelet analysis of ERP spectral bands using an ensemble of classifiers approach for early diagnosis of Alzheimer's disease
- Creators
- Robi Polikar - Electrical and Computer Engineering, Rowan University, Glassboro, NJ 08028, USAApostolos Topalis - Electrical and Computer Engineering, Rowan University, Glassboro, NJ 08028, USADeborah Green - Department of Psychology, Drexel University, Philadelphia, PA 19104, USAJohn Kounios - Department of Psychology, Drexel University, Philadelphia, PA 19104, USAChristopher M Clark - Department of Neurology, University of Pennsylvania, Philadelphia, PA 19104, USA
- Publication Details
- Computers in biology and medicine, v 37(4), pp 542-558
- Publisher
- Elsevier
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Psychological and Brain Sciences (Psychology)
- Web of Science ID
- WOS:000245156200012
- Scopus ID
- 2-s2.0-33846413521
- Other Identifier
- 991014877777804721
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Biology
- Computer Science, Interdisciplinary Applications
- Engineering, Biomedical
- Mathematical & Computational Biology