Information transfer between rich-club structures in the human brain. - Maksim Sharaev; Vyacheslav A. Orlov; Vadim L. Ushakov; Boris M. Velichkovsky (BICA, 2017)

Pattern Recognition Pipeline for Neuroimaging Data. - Maxim Sharaev; Alexander Andreev; Alexey Artemov; Evgeny Burnaev; Ekaterina Kondratyeva; Svetlana Sushchinskaya; Irina Samotaeva; Vladislav Gaskin; Alexander Bernstein (ANNPR, 2018)

Basic cognitive architectures and neuroimmune serum biomarkers in schizophrenia. - Vadim L. Ushakov; Maxim G. Sharaev; Irina K. Malashenkova; Sergey A. Krynskiy; Sergey I. Kartashov; Vyacheslav A. Orlov; Denis G. Malakhov; Nikita A. Hailov; Daniil P. Ogurtsov; Natalia V. Zakharova; Nikolay A. Didkovsky; Aleksandra V. Maslennikova; et al. (BICA, 2018)

Towards localization of radial traveling waves in the evoked and spontaneous MEG: A solution based on the intra-cortical propagation hypothesis. - Vitaly Verkhlyutov; Maxim Sharaev; Vladislav Balaev; Alexei Osadtchi; Vadim L. Ushakov; Lyudmila I. Skiteva; Boris M. Velichkovsky (BICA, 2018)

MRI-Based Diagnostics of Depression Concomitant with Epilepsy: In Search of the Potential Biomarkers. - Maksim Sharaev; Alexey Artemov; Ekaterina Kondratyeva; Svetlana Sushchinskaya; Evgeny Burnaev; Alexander Bernstein; Renat Akzhigitov; Alexander Andreev (DSAA, 2018)

Voxelwise 3D Convolutional and Recurrent Neural Networks for Epilepsy and Depression Diagnostics from Structural and Functional MRI Data. - Marina Pominova; Alexey Artemov; Maksim Sharaev; Ekaterina Kondrateva; Alexander Bernstein; Evgeny Burnaev (ICDM Workshops, 2018)

Learning Connectivity Patterns via Graph Kernels for fMRI-Based Depression Diagnostics. - Maksim Sharaev; Alexey Artemov; Ekaterina Kondrateva; Sergei Ivanov 002; Svetlana Sushchinskaya; Alexander Bernstein; Andrzej Cichocki; Evgeny Burnaev (ICDM Workshops, 2018)

Functional Brain Areas Mapping in Patients with Glioma Based on Resting-State fMRI Data Decomposition. - Maksim Sharaev; Alexander Smirnov; Tatiana Melnikova-Pitskhelauri; Vyacheslav A. Orlov; Evgeny Burnaev; Igor Pronin; David Pitskhelauri; Alexander Bernstein (ICDM Workshops, 2018)

Machine Learning pipeline for discovering neuroimaging-based biomarkers in neurology and psychiatry. - Alexander Bernstein; Evgeny Burnaev; Ekaterina Kondratyeva; Svetlana Sushchinskaya; Maxim Sharaev; Alexander Andreev; Alexey Artemov; Renat Akzhigitov (CoRR, 2018)

fMRI: preprocessing, classification and pattern recognition. - Maxim Sharaev; Alexander Andreev; Alexey Artemov; Alexander Bernstein; Evgeny Burnaev; Ekaterina Kondratyeva; Svetlana Sushchinskaya; Renat Akzhigitov (CoRR, 2018)

Weakly Supervised Fine Tuning Approach for Brain Tumor Segmentation Problem. - Sergey Pavlov; Alexey Artemov; Maksim Sharaev; Alexander Bernstein; Evgeny Burnaev (ICMLA, 2019)

3D Deformable Convolutions for MRI Classification. - Marina Pominova; Ekaterina Kondrateva; Maksim Sharaev; Alexander Bernstein; Sergey Pavlov; Evgeny Burnaev (ICMLA, 2019)

Topological data analysis in computer vision. - Alexander Bernstein; Eugeny Burnaev; Maxim Sharaev; Ekaterina Kondrateva; Oleg Kachan (ICMV, 2019)

Machine learning models reproducibility and validation for MR images recognition. - Ekaterina Kondrateva; Polina Belozerova; Maxim Sharaev; Evgeny Burnaev; Alexander Bernstein; Irina Samotaeva (ICMV, 2019)

Ensemble of 3D CNN Regressors with Data Fusion for Fluid Intelligence Prediction. - Marina Pominova; Anna Kuzina; Ekaterina Kondrateva; Svetlana Sushchinskaya; Evgeny Burnaev; Vyacheslav Yarkin; Maxim Sharaev (ABCD-NP@MICCAI, 2019)

Interpretation of 3D CNNs for Brain MRI Data Classification. - Maxim Kan; Ruslan Aliev; Anna Rudenko; Nikita Drobyshev; Nikita Petrashen; Ekaterina Kondrateva; Maxim Sharaev; Alexander Bernstein; Evgeny Burnaev (AIST (Supplement), 2020)

Domain shift in computer vision models for MRI data analysis: an overview. - Ekaterina Kondrateva; Marina Pominova; Maxim Sharaev; Alexander Bernstein; Evgeny Burnaev (ICMV, 2020)

Fader networks for domain adaptation on fMRI: ABIDE-II study. - Marina Pominova; Ekaterina Kondrateva; Maxim Sharaev; Alexander Bernstein; Evgeny Burnaev (ICMV, 2020)

Data-driven models and computational tools for neurolinguistics: a language technology perspective. - Ekaterina Artemova; Amir Bakarov; Aleksey Artemov; Evgeny Burnaev; Maxim Sharaev (CoRR, 2020)

Interpretable Deep Learning for Pattern Recognition in Brain Differences Between Men and Women. - Maxim Kan; Ruslan Aliev; Anna Rudenko; Nikita Drobyshev; Nikita Petrashen; Ekaterina Kondrateva; Maxim Sharaev; Alexander Bernstein; Evgeny Burnaev (CoRR, 2020)

Domain Shift in Computer Vision models for MRI data analysis: An Overview. - Ekaterina Kondrateva; Marina Pominova; Elena Popova; Maxim Sharaev; Alexander Bernstein; Evgeny Burnaev (CoRR, 2020)

Convolutional neural networks for automatic detection of Focal Cortical Dysplasia. - Ruslan Aliev; Ekaterina Kondrateva; Maxim Sharaev; Oleg Bronov; Alexey Marinets; Sergey Subbotin 002; Alexander Bernstein; Evgeny Burnaev (CoRR, 2020)

BRATS2021: Exploring Each Sequence in Multi-modal Input for Baseline U-net Performance. - Polina Druzhinina; Ekaterina Kondrateva; Arseny Bozhenko; Vyacheslav Yarkin; Maxim Sharaev; Anvar Kurmukov (BrainLes@MICCAI (1), 2021)

A Toolbox and Crowdsourcing Platform for Automatic Labeling of Independent Components in Electroencephalography. - Gurgen Soghoyan; Alexander Ledovsky; Maxim Nekrashevich; Olga Martynova 002; Irina Polikanova; Galina Portnova; Anna Rebreikina; Olga Sysoeva; Maxim Sharaev (Frontiers Neuroinformatics, 2021)

Autoencoders with deformable convolutions for latent representation of EEG spectrograms in classification tasks. - Maria Zubrikhina; Dmitrii Masnyi; Rifat Hamoudi; Hamid Alhaj; Bashar Issa; Almira Kustubaeva; Altyngul T. Kamzanova; Manzura Zholdassova; Alexander Bernstein; Evgeny Burnaev; Alexey Artemov; Maxim Sharaev (ICMV, 2022)

A machine learning investigation of factors that contribute to predicting cognitive performance: Difficulty level, reaction time and eye-movements. - Valentina Bachurina; Svetlana Sushchinskaya; Maxim Sharaev; Evgeny Burnaev; Marie Arsalidou (Decis. Support Syst., 2022)

New approaches to clinical electroencephalography analysis in typically developing children and children with autism. - Galina Portnova; Maxim Nekrashevich; M. V. Morozova; Olga Martynova 002; Maxim G. Sharaev (Cogn. Syst. Res., 2023)

MEGFormer: Enhancing Speech Decoding from Brain Activity Through Extended Semantic Representations. - Maria Boyko; Polina Druzhinina; Georgii Kormakov; Aleksandra Beliaeva; Maxim Sharaev (MICCAI (2), 2024)

Auditory event-related potential differentiates girls with Rett syndrome from their typically-developing peers with high accuracy: Machine learning study. - Maxim Sharaev; Maxim Nekrashevich; Daria Kostanian; Victoria Voinova; Olga Sysoeva (Cogn. Syst. Res., 2024)

Knowledge-informed randomized machine learning and data fusion for anomaly areas detection in multimodal 3D images. - Nadezhda Alsahanova; V. Yarkin; E. Spodarev; O. Bronov; V. Bychenko; A. Marinets; E. Syrkashev; O. Karpov; Evgeny Burnaev; Alexander Bernstein; V. Alferova; Maxim Sharaev (Inf. Sci., 2025)

A hierarchical algorithm with randomized learning for robust tissue segmentation and classification in digital pathology. - Svetlana Illarionova; Rifat A. Hamoudi; M. Zapevalina; I. Fedin; Nadezhda Alsahanova; Alexander Bernstein; Evgeny Burnaev; V. Alferova; Ekaterina Khrameeva; D. Shadrin; I. Talaat; Ahmed Bouridane; et al. (Inf. Sci., 2025)

Biologically Inspired Deep Learning Approaches for Fetal Ultrasound Image Classification. - Rinat Prochii; Elizaveta Dakhova; Pavel Birulin; Maxim Sharaev (CoRR, 2025)

Integrating Radiomics with Deep Learning Enhances Multiple Sclerosis Lesion Delineation. - Nadezhda Alsahanova; Pavel Bartenev; Maksim Sharaev; Milos Ljubisavljevic; Taleb Al. Mansoori; Yauhen Statsenko (CoRR, 2025)