MOTIVATION: Self-organizing maps (SOMs) are readily available bioinformatics methods for clustering and visualizing high-dimensional data, provided that such biological information is previously transformed to fixed-size, metric-based vectors. To inc...
IEEE transactions on neural networks and learning systems
Oct 16, 2014
Sparse representations using learned dictionaries are being increasingly used with success in several data processing and machine learning applications. The increasing need for learning sparse models in large-scale applications motivates the developm...
IEEE journal of biomedical and health informatics
Oct 8, 2014
The free text in electronic health records (EHRs) conveys a huge amount of clinical information about health state and patient history. Despite a rapidly growing literature on the use of machine learning techniques for extracting this information, li...
In this paper, a novel label propagation (LP) method is presented, called the manifold adaptive label propagation (MALP) method, which is to extend original LP by integrating sparse representation constraint into regularization framework of LP method...
IEEE transactions on neural networks and learning systems
Jul 17, 2014
In this paper, an optimized multilayer feed-forward network (MLFN) is developed to construct a soft sensor for controlling naphtha dry point. To overcome the two main flaws in the structure and weight of MLFNs, which are trained by a back-propagation...
This paper considers microarray gene expression data clustering using a novel two stage meta-heuristic algorithm based on the concept of α-planes in general type-2 fuzzy sets. The main aim of this research is to present a powerful data clustering app...
Neural networks : the official journal of the International Neural Network Society
Jun 9, 2014
Although it is very important to scrutinize recurrent structures of neural networks for elucidating brain functions, conventional methods often have difficulty in characterizing global loops within a network systematically. Here we applied the Hodge-...
IEEE journal of biomedical and health informatics
Jun 1, 2025
Single-cell multi-omics sequencing technology comprehensively considers various molecular features to reveal the complexity of cells information. The clustering analysis of multi-omics data provides new insight into cellular heterogeneity. However, m...
Studies in health technology and informatics
May 15, 2025
In this study, we analyzed voice of customer (VOC) data for an AI-based early warning system from healthcare providers using the BERTopic framework for effective topic modeling. A preprocessing pipeline was implemented, incorporating techniques such ...
MOTIVATION: Single-cell RNA sequencing (scRNA-seq) analysis relies heavily on effective clustering to facilitate numerous downstream applications. Although several machine learning methods have been developed to enhance single-cell clustering, most a...