no code implementations • 23 Sep 2022 • Oleg Kachan, Alexander Bernstein
Most approaches to the estimation of brain functional connectivity from the functional magnetic resonance imaging (fMRI) data rely on computing some measure of statistical dependence, or more generally, a distance between univariate representative time series of regions of interest (ROIs) consisting of multiple voxels.
2 code implementations • EMNLP 2021 • Laida Kushnareva, Daniil Cherniavskii, Vladislav Mikhailov, Ekaterina Artemova, Serguei Barannikov, Alexander Bernstein, Irina Piontkovskaya, Dmitri Piontkovski, Evgeny Burnaev
The impressive capabilities of recent generative models to create texts that are challenging to distinguish from the human-written ones can be misused for generating fake news, product reviews, and even abusive content.
1 code implementation • 20 Oct 2020 • Ruslan Aliev, Ekaterina Kondrateva, Maxim Sharaev, Oleg Bronov, Alexey Marinets, Sergey Subbotin, Alexander Bernstein, Evgeny Burnaev
Focal cortical dysplasia (FCD) is one of the most common epileptogenic lesions associated with cortical development malformations.
1 code implementation • 14 Oct 2020 • Marina Pominova, Ekaterina Kondrateva, Maxim Sharaev, Alexander Bernstein, Evgeny Burnaev
ABIDE is the largest open-source autism spectrum disorder database with both fMRI data and full phenotype description.
1 code implementation • 14 Oct 2020 • Ekaterina Kondrateva, Marina Pominova, Elena Popova, Maxim Sharaev, Alexander Bernstein, Evgeny Burnaev
Machine learning and computer vision methods are showing good performance in medical imagery analysis.
1 code implementation • 20 Jun 2020 • Maxim Kan, Ruslan Aliev, Anna Rudenko, Nikita Drobyshev, Nikita Petrashen, Ekaterina Kondrateva, Maxim Sharaev, Alexander Bernstein, Evgeny Burnaev
Deep learning shows high potential for many medical image analysis tasks.
2 code implementations • 5 Nov 2019 • Marina Pominova, Ekaterina Kondrateva, Maksim Sharaev, Sergey Pavlov, Alexander Bernstein, Evgeny Burnaev
Deep learning convolutional neural networks have proved to be a powerful tool for MRI analysis.
1 code implementation • 5 Nov 2019 • Sergey Pavlov, Alexey Artemov, Maksim Sharaev, Alexander Bernstein, Evgeny Burnaev
Segmentation of tumors in brain MRI images is a challenging task, where most recent methods demand large volumes of data with pixel-level annotations, which are generally costly to obtain.
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.
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.
no code implementations • 17 Jun 2017 • Alexander Kuleshov, Alexander Bernstein, Evgeny Burnaev, Yury Yanovich
The latter allows solving the robot localization problem as the Kalman filtering problem.
no code implementations • 11 Jun 2017 • Vladislav Ishimtsev, Ivan Nazarov, Alexander Bernstein, Evgeny Burnaev
Anomalies in time-series data give essential and often actionable information in many applications.