Topological pattern recognition of severe Alzheimer's disease via regularized supervised learning of EEG complexity
Alzheimer's disease (AD) is a progressive brain disorder with gradual memory loss that
correlates to cognitive deficits in the elderly population. Recent studies have shown the …
correlates to cognitive deficits in the elderly population. Recent studies have shown the …
FFTPSOGA: Fast Fourier Transform with particle swarm optimization and genetic algorithm approach for pattern identification of brain responses in multi subject fMRI …
Abstract Functional Magnetic Resonance Imaging (fMRI) is the popular technique where it is
possible to capture neural activity in brain regions when subjected to different stimuli …
possible to capture neural activity in brain regions when subjected to different stimuli …
Multivariate pattern analysis and the search for neural representations
B Gessell, B Geib, F De Brigard - Synthese, 2021 - Springer
Multivariate pattern analysis, or MVPA, has become one of the most popular analytic
methods in cognitive neuroscience. Since its inception, MVPA has been heralded as offering …
methods in cognitive neuroscience. Since its inception, MVPA has been heralded as offering …
Fast, accurate, and stable feature selection using neural networks
J Deraeve, WH Alexander - Neuroinformatics, 2018 - Springer
Multi-voxel pattern analysis often necessitates feature selection due to the high dimensional
nature of neuroimaging data. In this context, feature selection techniques serve the dual …
nature of neuroimaging data. In this context, feature selection techniques serve the dual …
Classification of cognitive states using clustering-split time series framework
Over the last two decades, functional Magnetic Resonance Imaging (fMRI) has provided
immense data about the dynamics of the brain. Ongoing developments in machine learning …
immense data about the dynamics of the brain. Ongoing developments in machine learning …
Stable multivariate lesion symptom map**
Multivariate lesion-symptom map** (MLSM) considers lesion information across the entire
brain to predict impairments. The strength of this approach is also its weakness …
brain to predict impairments. The strength of this approach is also its weakness …
Excellence is a habit: Enhancing predictions of language impairment by identifying stable features in clinical perfusion scans
Perfusion images guide acute stroke management, yet few studies have been able to
systematically investigate CT perfusion collected during routine care because the measures …
systematically investigate CT perfusion collected during routine care because the measures …
fastHDMI: Fast Mutual Information Estimation for High-Dimensional Data
In this paper, we introduce fastHDMI, a Python package designed for efficient variable
screening in high-dimensional datasets, particularly neuroimaging data. This work pioneers …
screening in high-dimensional datasets, particularly neuroimaging data. This work pioneers …
Fast retrieval of fMRI data for real-time applications: improving the transfer time through direct connection
Background Anorexia nervosa is a severe psychiatric disorder with a heterogeneous course
with one of the highest rates of morbidity and mortality of all psychiatric disorders. Little is …
with one of the highest rates of morbidity and mortality of all psychiatric disorders. Little is …
Evolutionary Algorithms' Feature Selection Stability Improvement System
Y Liu, X Diao, J Cao, L Zhang - … Conference, BIC-TA 2017, Harbin, China …, 2017 - Springer
In order to improve the feature selection stability based on evolutionary algorithms, an
evolutionary algorithms' feature selection stability improvement system is proposed. Three …
evolutionary algorithms' feature selection stability improvement system is proposed. Three …