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Journal article
ERP based decision fusion for AD diagnosis across cohorts
Conference proceedings (IEEE Engineering in Medicine and Biology Society. Conf.), v 2009, pp 2494-2497
2009
PMID: 19965206
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
As the average life expectancy increases, particularly in developing countries, prevalence of neurodegenerative diseases has also increased. This trend is especially alarming for Alzheimer's disease (AD); as there is no cure to stop or reverse the effects of AD. However, recent pharmacological advances can slow the progression of AD, but only if AD is diagnosed at early stages. We have previously introduced an ensemble of classifiers based approach for combining event related potentials obtained from different electrode locations as an effective approach for early diagnosis of AD. We further expand this approach and analyze its robustness and stability in two ways: comparing the diagnostic accuracy on hand selected and cleaned data vs. standard automated preprocessing, but more importantly, comparing the diagnostic accuracy on two different cohorts, whose data are collected under different settings: a research university lab and a community clinic.
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Details
- Title
- ERP based decision fusion for AD diagnosis across cohorts
- Creators
- Metin Ahiskali - Signal Processing and Pattern Recognition Laboratory, Department of Electrical and Computer Eng. at Rowan University, Glassboro, NJ 08028, USA. mahiskali@gmail.comDeborah GreenJohn KouniosChristopher M ClarkRobi Polikar
- Publication Details
- Conference proceedings (IEEE Engineering in Medicine and Biology Society. Conf.), v 2009, pp 2494-2497
- Publisher
- The Institute of Electrical and Electronics Engineers, Inc. (IEEE); United States
- Grant note
- AG10124 / NIA NIH HHS AG022272 / NIA NIH HHS
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Psychological and Brain Sciences (Psychology)
- Web of Science ID
- WOS:000280543601361
- Scopus ID
- 2-s2.0-77950982482
- Other Identifier
- 9781424432967; 1424432960; 991014878209004721
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Engineering, Biomedical