AI Medical Compendium Journal:
Frontiers in neuroinformatics

Showing 1 to 10 of 16 articles

Identifying natural inhibitors against FUS protein in dementia through machine learning, molecular docking, and dynamics simulation.

Frontiers in neuroinformatics
Dementia, a complex and debilitating spectrum of neurodegenerative diseases, presents a profound challenge in the quest for effective treatments. The FUS protein is well at the center of this problem, as it is frequently dysregulated in the various d...

Leveraging deep learning for robust EEG analysis in mental health monitoring.

Frontiers in neuroinformatics
INTRODUCTION: Mental health monitoring utilizing EEG analysis has garnered notable interest due to the non-invasive characteristics and rich temporal information encoded in EEG signals, which are indicative of cognitive and emotional conditions. Conv...

Classification of ROI-based fMRI data in short-term memory tasks using discriminant analysis and neural networks.

Frontiers in neuroinformatics
Understanding brain function relies on identifying spatiotemporal patterns in brain activity. In recent years, machine learning methods have been widely used to detect connections between regions of interest (ROIs) involved in cognitive functions, as...

Comparing feature selection and machine learning approaches for predicting methylation from genetic variation.

Frontiers in neuroinformatics
INTRODUCTION: Pharmacogenetics currently supports clinical decision-making on the basis of a limited number of variants in a few genes and may benefit paediatric prescribing where there is a need for more precise dosing. Integrating genomic informati...

Introducing Region Based Pooling for handling a varied number of EEG channels for deep learning models.

Frontiers in neuroinformatics
INTRODUCTION: A challenge when applying an artificial intelligence (AI) deep learning (DL) approach to novel electroencephalography (EEG) data, is the DL architecture's lack of adaptability to changing numbers of EEG channels. That is, the number of ...

NeuroDecodeR: a package for neural decoding in R.

Frontiers in neuroinformatics
Neural decoding is a powerful method to analyze neural activity. However, the code needed to run a decoding analysis can be complex, which can present a barrier to using the method. In this paper we introduce a package that makes it easy to perform d...