Neural networks : the official journal of the International Neural Network Society
39893803
A graph is a fundamental mathematical structure in characterizing relations between different objects and has been widely used on various learning tasks. Most methods implicitly assume a given graph to be accurate and complete. However, real data is ...
Neural networks : the official journal of the International Neural Network Society
39892354
The attention towards clustering using anchor graph has grown due to its effectiveness and efficiency. As the most representative points in original data, anchors are also regarded as connecting the sample space to the label space. However, when ther...
Neural networks : the official journal of the International Neural Network Society
39889375
While self-labeled methods can exploit unlabeled and labeled instances to train classifiers, they are also restricted by the labeled instance number and distribution. SEG-SSC, k-means-SSC, LC-SSC, and LCSEG-SSC are sophisticated solutions for overcom...
Neural networks : the official journal of the International Neural Network Society
39884175
Unsupervised domain adaptation (UDA) aims to annotate unlabeled target domain samples using transferable knowledge learned from the labeled source domain. Optimal transport (OT) is a widely adopted probability metric in transfer learning for quantify...
BACKGROUND: Single-cell RNA sequencing (scRNA-seq) has transformed biological research by offering new insights into cellular heterogeneity, developmental processes, and disease mechanisms. As scRNA-seq technology advances, its role in modern biology...
BMC medical informatics and decision making
39875929
INTRODUCTION: Unsupervised feature learning methods inspired by natural language processing (NLP) models are capable of constructing patient-specific features from longitudinal Electronic Health Records (EHR).
UNLABELLED: Bacterial typing at whole-genome scales is now feasible owing to decreasing costs in high-throughput sequencing and the recent advances in computation. The unprecedented resolution of whole-genome typing is achieved by genotyping the vari...
Alzheimer's & dementia : the journal of the Alzheimer's Association
39868506
INTRODUCTION: Current models of Alzheimer's disease (AD) progression assume a common pattern and pathology, oversimplifying the heterogeneity of clinical AD.
BACKGROUND: The application of natural language processing in medicine has increased significantly, including tasks such as information extraction and classification. Natural language processing plays a crucial role in structuring free-form radiology...
The current work introduces the hybrid ensemble framework for the detection and segmentation of colorectal cancer. This framework will incorporate both supervised classification and unsupervised clustering methods to present more understandable and a...