Abstract: Evidential clustering is a promising clustering framework using Dempster–Shafer belief function theory to model uncertain data. However, evidential clustering needs to estimate more ...

Abstract: Recently, clustering algorithms based on deep AutoEncoder attract lots of attention due to their excellent clustering performance. On the other hand, the success of PCA-Kmeans and spectral ...

Insomnia disorder (ID) is neurobiologically heterogeneous and often eludes characterization by traditional group-level neuroimaging. Subtyping based on neuroimaging and clinical data offers a ...

Treatment response prediction remains one of the most pressing challenges in precision psychiatry, where patient heterogeneity and complex biomarker interactions limit the reliability of conventional ...

scVAG is an innovative framework that integrates Variational Autoencoder (VAE) and Graph Attention Autoencoder (GATE) models for enhanced analysis of single-cell gene expression data. Built upon the ...

Spatially resolved transcriptomics (SRT) technologies, such as spatial transcriptomics (ST) (Ståhl et al., 2016), 10x Visium, and Slide-seqV2 (Stickels et al., 2021), can measure the transcript ...

scAce is consisted of three major steps, a pre-training step based on a variational autoencoder, a cluster initialization step to obtain initial cluster labels, and an adaptive cluster merging step to ...

College of Materials and Chemistry & Chemical Engineering, Chengdu University of Technology, Chengdu, Sichuan 610059, P. R. China ...