Classifying cognitive profiles using machine learning with privileged information in mild cognitive impairment
- Submitting institution
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Birmingham City University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 11Z_OP_D0053
- Type
- D - Journal article
- DOI
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10.3389/fncom.2016.00117
- Title of journal
- Frontiers in Computational Neuroscience
- Article number
- 117
- First page
- -
- Volume
- 10
- Issue
- 11
- ISSN
- 1662-5188
- Open access status
- Compliant
- Month of publication
- -
- Year of publication
- 2016
- URL
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https://www.frontiersin.org/articles/10.3389/fncom.2016.00117/
- Supplementary information
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- Request cross-referral to
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- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
-
- Research group(s)
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- Citation count
- 6
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- A novel Machine Learning-based technique is proposed which detects early signs of dementia using cognitive skills in Mild Cognitive Impairment (MCI) patients. The proposed method outperforms the baseline framework that relies on cognitive data only. The study has inspired more machine learning-based techniques in the area of neuroimaging which combines fMRI with imaging data to perform automatic diagnosis of disease that thought to be impossible to identify based on imaging data alone. This paper was cited by 7 research papers, I provide below DOIs of the citing papers: https://doi.org/10.1109/TBME.2018.2889398 , https://doi.org/10.1016/j.neunet.2019.09.039 ,https://doi.org/10.1007/s11517-019-01974-3 ,https://doi.org/10.1016/j.nic.2017.06.010, https://doi.org/10.1007/s00138-020-01058-5, https://doi.org/10.1186/s12911-019-0858-0 , https://doi: 10.1109/CICT48419.2019.9066233.
- Author contribution statement
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- Non-English
- No
- English abstract
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