AI Medical Compendium Journal:
Frontiers in computational neuroscience

Showing 1 to 10 of 14 articles

Automated karyogram analysis for early detection of genetic and neurodegenerative disorders: a hybrid machine learning approach.

Frontiers in computational neuroscience
Anomalous chromosomes are the cause of genetic diseases such as cancer, Alzheimer's, Parkinson's, epilepsy, and autism. Karyotype analysis is the standard procedure for diagnosing genetic disorders. Identifying anomalies is often costly, time-consumi...

FacialNet: facial emotion recognition for mental health analysis using UNet segmentation with transfer learning model.

Frontiers in computational neuroscience
Facial emotion recognition (FER) can serve as a valuable tool for assessing emotional states, which are often linked to mental health. However, mental health encompasses a broad range of factors that go beyond facial expressions. While FER provides i...

Neuro-environmental interactions: a time sensitive matter.

Frontiers in computational neuroscience
INTRODUCTION: The assessment of resting state (rs) neurophysiological dynamics relies on the control of sensory, perceptual, and behavioral environments to minimize variability and rule-out confounding sources of activation during testing conditions....

Machine learning hypothesis-generation for patient stratification and target discovery in rare disease: our experience with Open Science in ALS.

Frontiers in computational neuroscience
INTRODUCTION: Advances in machine learning (ML) methodologies, combined with multidisciplinary collaborations across biological and physical sciences, has the potential to propel drug discovery and development. Open Science fosters this collaboration...

Bio-inspired circular latent spaces to estimate objects' rotations.

Frontiers in computational neuroscience
This paper proposes a neural network model that estimates the rotation angle of unknown objects from RGB images using an approach inspired by biological neural circuits. The proposed model embeds the understanding of rotational transformations into i...

Intra- and Inter-subject Variability in EEG-Based Sensorimotor Brain Computer Interface: A Review.

Frontiers in computational neuroscience
Brain computer interfaces (BCI) for the rehabilitation of motor impairments exploit sensorimotor rhythms (SMR) in the electroencephalogram (EEG). However, the neurophysiological processes underpinning the SMR often vary over time and across subjects....

Comparing Cyclicity Analysis With Pre-established Functional Connectivity Methods to Identify Individuals and Subject Groups Using Resting State fMRI.

Frontiers in computational neuroscience
The resting state fMRI time series appears to have cyclic patterns, which indicates presence of cyclic interactions between different brain regions. Such interactions are not easily captured by pre-established resting state functional connectivity me...

Bio-inspired Analysis of Deep Learning on Not-So-Big Data Using Data-Prototypes.

Frontiers in computational neuroscience
Deep artificial neural networks are feed-forward architectures capable of very impressive performances in diverse domains. Indeed stacking multiple layers allows a hierarchical composition of local functions, providing efficient compact mappings. Com...