Ensemble of 3D CNN regressors with data fusion for fluid intelligence prediction

no code implementations • 25 May 2019 • Marina Pominova, Anna Kuzina, Ekaterina Kondrateva, Svetlana Sushchinskaya, Maxim Sharaev, Evgeny Burnaev, and Vyacheslav Yarkin

In this work, we aim at predicting children's fluid intelligence scores based on structural T1-weighted MR images from the largest long-term study of brain development and child health.

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

no code implementations • 26 Apr 2018 • Alexander Bernstein, Evgeny Burnaev, Ekaterina Kondratyeva, Svetlana Sushchinskaya, Maxim Sharaev, Alexander Andreev, Alexey Artemov, Renat Akzhigitov

We consider a problem of diagnostic pattern recognition/classification from neuroimaging data.

BIG-bench Machine Learning Classification +1

fMRI: preprocessing, classification and pattern recognition

no code implementations • 26 Apr 2018 • Maxim Sharaev, Alexander Andreev, Alexey Artemov, Alexander Bernstein, Evgeny Burnaev, Ekaterina Kondratyeva, Svetlana Sushchinskaya, Renat Akzhigitov

As machine learning continues to gain momentum in the neuroscience community, we witness the emergence of novel applications such as diagnostics, characterization, and treatment outcome prediction for psychiatric and neurological disorders, for instance, epilepsy and depression.

Classification General Classification