AIMC Topic: Neural Networks, Computer

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An attribution graph-based interpretable method for CNNs.

Neural networks : the official journal of the International Neural Network Society
Convolutional Neural Networks (CNNs) have demonstrated outstanding performance in various domains, such as face recognition, object detection, and image segmentation. However, the lack of transparency and limited interpretability inherent in CNNs pos...

Human-robot interaction in motor imagery: A system based on the STFCN for unilateral upper limb rehabilitation assistance.

Journal of neuroscience methods
BACKGROUND: Rehabilitation training based on the brain-computer interface of motor imagery (MI-BCI) can help restore the connection between the brain and movement. However, the performance of most popular MI-BCI system is coarse-level, which means th...

Enhancing schizophrenia phenotype prediction from genotype data through knowledge-driven deep neural network models.

Genomics
This article explores deep learning model design, drawing inspiration from the omnigenic model and genetic heterogeneity concepts, to improve schizophrenia prediction using genotype data. It introduces an innovative three-step approach leveraging neu...

Development and validation of a two-stage convolutional neural network algorithm for segmentation of MRI white matter hyperintensities for longitudinal studies in CADASIL.

Computers in biology and medicine
BACKGROUND: Segmentation of white matter hyperintensities (WMH) in CADASIL, one of the most severe cerebral small vessel disease of genetic origin, is challenging.

Brain-GCN-Net: Graph-Convolutional Neural Network for brain tumor identification.

Computers in biology and medicine
BACKGROUND: The intersection of artificial intelligence and medical image analysis has ushered in a new era of innovation and changed the landscape of brain tumor detection and diagnosis. Correct detection and classification of brain tumors based on ...

GCGACNN: A Graph Neural Network and Random Forest for Predicting Microbe-Drug Associations.

Biomolecules
The interaction between microbes and drugs encompasses the sourcing of pharmaceutical compounds, microbial drug degradation, the development of , and the impact of on host drug metabolism and immune modulation. These interactions significantly impac...

Research into the Applications of a Multi-Scale Feature Fusion Model in the Recognition of Abnormal Human Behavior.

Sensors (Basel, Switzerland)
Due to the increasing severity of aging populations in modern society, the accurate and timely identification of, and responses to, sudden abnormal behaviors of the elderly have become an urgent and important issue. In the current research on compute...

Prediction models for retinopathy of prematurity occurrence based on artificial neural network.

BMC ophthalmology
INTRODUCTION: Early prediction and timely treatment are essential for minimizing the risk of visual loss or blindness of retinopathy of prematurity, emphasizing the importance of ROP screening in clinical routine.

Performance of convolutional neural network (CNN) and performance influencing factors for wood species classification of Lepidobalanus growing in Korea.

Scientific reports
This study aimed to investigate the performance and factors affecting the species classification of convolutional neural network (CNN) architecture using whole-part and earlywood-part cross-sectional datasets of six Korean Quercus species. The accura...

An Effective Deep Learning Framework for Fall Detection: Model Development and Study Design.

Journal of medical Internet research
BACKGROUND: Fall detection is of great significance in safeguarding human health. By monitoring the motion data, a fall detection system (FDS) can detect a fall accident. Recently, wearable sensors-based FDSs have become the mainstream of research, w...