Conference proceeding
Majority vote and decision template based ensemble classifiers trained on event related potentials for early diagnosis of Alzheimer's disease
2006 IEEE International Conference on Acoustics, Speech and Signal Processing, Vols 1-13, pp.5759-5762
International Conference on Acoustics Speech and Signal Processing (ICASSP)
01 Jan 2006
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
With the rapid increase in the population of elderly individuals affected by Alzheimer's disease, the need for an accurate, inexpensive and non-intrusive diagnostic biomarker that can be made available to community healthcare providers presents itself as a major public health concern. The feasibility of EEG as such a biomarker has gained a renewed attention as several recent studies, including our previous efforts, reported promising results. In this paper we present our preliminary results on using wavelet coefficients of event related potentials along with an ensemble of classifiers combined with majority vote and decision templates.
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Details
- Title
- Majority vote and decision template based ensemble classifiers trained on event related potentials for early diagnosis of Alzheimer's disease
- Creators
- Nicholas StepenoskyDeborah GreenJohn KouniosChristopher M. ClarkRobi PolikarIEEE
- Publication Details
- 2006 IEEE International Conference on Acoustics, Speech and Signal Processing, Vols 1-13, pp.5759-5762
- Series
- International Conference on Acoustics Speech and Signal Processing (ICASSP)
- Publisher
- IEEE
- Number of pages
- 4
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Psychology
- Identifiers
- 991019173704904721
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- Web of Science research areas
- Acoustics
- Computer Science, Artificial Intelligence
- Engineering, Electrical & Electronic
- Imaging Science & Photographic Technology