Machine Learning pipeline for discovering neuroimaging-based biomarkers in neurology and psychiatry

2018/04/26 by Alexander Bernstein, Evgeny Burnaev, Bernstein, Alexander +14
Computer Science · Materials Science · Neuroscience · #Applications (stat.AP) #Brain Tumor Detection and Classification #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Functional Brain Connectivity Studies #Machine Learning in Healthcare #Machine Learning in Materials Science

paper · pdf · doi:10.48550/arxiv.1804.10163

openalex publication_date 2018/04/26 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

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.

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