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Found 8 papers, 4 papers with code
Personalized graph feature-based multi-omics data integration for cancer subtype identification
Cancer is a highly heterogeneous disease with significant variability in molecular features and clinical outcomes, making diagnosis and treatment challenging.
A Structural Feature-Based Approach for Comprehensive Graph Classification
The increasing prevalence of graph-structured data across various domains has intensified greater interest in graph classification tasks.
Federated Learning and Differential Privacy Techniques on Multi-hospital Population-scale Electrocardiogram Data
Our results show that the performance achieved using our implementation of the FL approach is comparable to that of the pooled approach, where the model is trained over the aggregating data from all hospitals.
State-transition dynamics of resting-state functional magnetic resonance imaging data: Model comparison and test-to-retest analysis
Electroencephalogram (EEG) microstate analysis entails finding dynamics of quasi-stable and generally recurrent discrete states in multichannel EEG time series data and relating properties of the estimated state-transition dynamics to observables such as cognition and behavior.
BdSL36: A Dataset for Bangladeshi Sign Letters Recognition
Bangladeshi Sign Language (BdSL) is a commonly used medium of communication for the hearing-impaired people in Bangladesh.
Cancer diagnosis in histopathological image: CNN based approach
Modern medical image processing techniques work on histopathology images captured by a microscope, and then analyze them by using different algorithms and methods.
VStegNET: Video Steganography Networkusing Spatio-Temporal features andMicro-Bottleneck
Traditional image steganography techniques hide the secret image intohigh-frequency regions of the cover images.
3D human action analysis and recognition through GLAC descriptor on 2D motion and static posture images
We then characterize the action video by extracting the Gradient Local Auto-Correlations (GLAC) features from the SHIs and the MHIs.
