AI Medical Compendium Topic:
Cluster Analysis

Clear Filters Showing 611 to 620 of 1323 articles

JSOM: Jointly-evolving self-organizing maps for alignment of biological datasets and identification of related clusters.

PLoS computational biology
With the rapid advances of various single-cell technologies, an increasing number of single-cell datasets are being generated, and the computational tools for aligning the datasets which make subsequent integration or meta-analysis possible have beco...

Understanding the message passing in graph neural networks via power iteration clustering.

Neural networks : the official journal of the International Neural Network Society
The mechanism of message passing in graph neural networks (GNNs) is still mysterious. Apart from convolutional neural networks, no theoretical origin for GNNs has been proposed. To our surprise, message passing can be best understood in terms of powe...

Machine Learning Analysis of Naïve B-Cell Receptor Repertoires Stratifies Celiac Disease Patients and Controls.

Frontiers in immunology
Celiac disease (CeD) is a common autoimmune disorder caused by an abnormal immune response to dietary gluten proteins. The disease has high heritability. HLA is the major susceptibility factor, and the HLA effect is mediated via presentation of deami...

Nonparametric machine learning for precision medicine with longitudinal clinical trials and Bayesian additive regression trees with mixed models.

Statistics in medicine
Precision medicine is an active area of research that could offer an analytic paradigm shift for clinical trials and the subsequent treatment decisions based on them. Clinical trials are typically analyzed with the intent of discovering beneficial tr...

DeepVISP: Deep Learning for Virus Site Integration Prediction and Motif Discovery.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Approximately 15% of human cancers are estimated to be attributed to viruses. Virus sequences can be integrated into the host genome, leading to genomic instability and carcinogenesis. Here, a new deep convolutional neural network (CNN) model is deve...

Dual self-paced multi-view clustering.

Neural networks : the official journal of the International Neural Network Society
By utilizing the complementary information from multiple views, multi-view clustering (MVC) algorithms typically achieve much better clustering performance than conventional single-view methods. Although in this field, great progresses have been made...

R-HEFS: Rough set based heterogeneous ensemble feature selection method for medical data classification.

Artificial intelligence in medicine
Feature selection is one of the trustworthy processes of dimensionality reduction technique to select a subset of relevant and non-redundant features from large datasets. Ensemble feature selection (EFS) approach is a recent technique aiming at accum...

Combinatorial K-Means Clustering as a Machine Learning Tool Applied to Diabetes Mellitus Type 2.

International journal of environmental research and public health
A new original procedure based on k-means clustering is designed to find the most appropriate clinical variables able to efficiently separate into groups similar patients diagnosed with diabetes mellitus type 2 (DMT2) and underlying diseases (arteria...

Evolutionary Algorithm based Ensemble Extractive Summarization for Developing Smart Medical System.

Interdisciplinary sciences, computational life sciences
The amount of information in the scientific literature of the bio-medical domain is growing exponentially, which makes it difficult in developing a smart medical system. Summarization techniques help for efficient searching and understanding of relev...

A computer-aided approach for automatic detection of breast masses in digital mammogram via spectral clustering and support vector machine.

Physical and engineering sciences in medicine
Breast cancer continues to be a widespread health concern all over the world. Mammography is an important method in the early detection of breast abnormalities. In recent years, using an automatic Computer-Aided Detection (CAD) system based on image ...