Using Echo State Networks for Classification : A Case Study in Parkinson's Disease Diagnosis
- Submitting institution
-
University of York
- Unit of assessment
- 12 - Engineering
- Output identifier
- 55025888
- Type
- D - Journal article
- DOI
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10.1016/j.artmed.2018.02.002
- Title of journal
- Artificial intelligence in medicine
- Article number
- -
- First page
- 53
- Volume
- 86
- Issue
- -
- ISSN
- 0933-3657
- Open access status
- Compliant
- Month of publication
- February
- Year of publication
- 2018
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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2
- Research group(s)
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B - Intelligent Systems and Nano-Science
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper describes, for the first time, how echo state networks can generate classifiers substantially faster than other types of machine learning and are therefore well suited to real-time monitoring of Parkinson’s disease. This work has led to partnerships between the University of York spin-out ClearSky Medical Diagnostics (clearskymd.com), MAAB (maab-group.com) and Shimmer Sensing (shimmersensing.com) to develop the next generation of medical devices for monitoring the side-effects of medication for Parkinson’s disease.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -