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Modern diagnostics and prognosis of treatment in such areas as neurosurgery, neurology and psychiatry are impossible without the analysis of images obtained in different modalities: structural and functional magnetic resonance imaging (MRI), positron emission tomography (PET), as well as data on electrical activity of the brain (EEG). In psychophysiological studies of educational process and during training of cyber-sportsmen it is possible to use wearable electronics and eye tracking devices for data collection. Classical statistical analysis, as well as machine learning, applied to data with such complex structure and high dimensionality, is a challenge for data analysis engineers. In this presentation I will highlight the current state of the art in this field, achieved by the scientific group ADASE from Skoltech in such tasks as: effective dimension reduction of fMRI data for mapping the functional areas of the brain in surgical planning and neuronavigation, segmentation of three-dimensional MRI images to detect lesions, etc. Recent breakthroughs in Data science (deep neural networks including convolutional and tensor networks, geometrical and topological data analysis, statistical methods in functional imaging consisting of EEG/MEG data or time series of 3D images, etc.) allowed not only to create effective diagnostic and prognostic tools but also created prerequisites for alleviating early detection of mental disorders and brain tumors, accelerate the search for life-saving pharmaceuticals, and provide insights about the molecular pathways of the neurodegenerative diseases. The workshop is oriented to all potential applications of data science technologies in feature extraction, classification, recognition, segmentation, enhancing, clustering, anomaly detection, and prediction of neurodegenerative disease states – as applied to the various biomedical time series and images of different nature, especially to multi-modal brain data (X-ray, MRI/fMRI/CT, EEG/MEG, and biomarker assays). Special attention will be paid to Biomedical signals processing for diagnostics and treatment outcome prediction and Natural language processing for case records and medical history. Professor Evgeny Burnaev – contact person, E.Burnaev@skoltech.ru
Professor Andrzej Cichocki, A.Cichocki@skoltech.ru
Professor Alexander Bernstein, A.Bernstein@skoltech.ru
Leading researcher Maxim Sharaev, M.Sharaev@skoltech.ru