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Machine Learning pipeline for discovering neuroimaging-based biomarkers in neurology and psychiatry (1804.10163v1)
Published 26 Apr 2018 in cs.CV and stat.AP
Abstract: We consider a problem of diagnostic pattern recognition/classification from neuroimaging data. We propose a common data analysis pipeline for neuroimaging-based diagnostic classification problems using various ML algorithms and processing toolboxes for brain imaging. We illustrate the pipeline application by discovering new biomarkers for diagnostics of epilepsy and depression based on clinical and MRI/fMRI data for patients and healthy volunteers.
- Alexander Bernstein (12 papers)
- Evgeny Burnaev (189 papers)
- Ekaterina Kondratyeva (2 papers)
- Svetlana Sushchinskaya (3 papers)
- Maxim Sharaev (9 papers)
- Alexander Andreev (8 papers)
- Alexey Artemov (29 papers)
- Renat Akzhigitov (2 papers)