AIMC Topic:
Cluster Analysis

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Clustering Nursing Sentences - Comparing Three Sentence Embedding Methods.

Studies in health technology and informatics May 25, 2022
In health sciences, high-quality text embeddings may augment qualitative data analysis of large amounts of text by enabling, e.g., searching and clustering of health information. This study aimed to evaluate three different sentence-level embedding m...
Cluster Analysis Natural Language Processing Unified Medical Language System Humans Language
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Dynamic community detection over evolving networks based on the optimized deep graph infomax.

Chaos (Woodbury, N.Y.) May 1, 2022
As complex systems, dynamic networks have obvious nonlinear features. Detecting communities in dynamic networks is of great importance for understanding the functions of networks and mining evolving relationships. Recently, some network embedding-bas...
Neural Networks, Computer Algorithms Cluster Analysis
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Deep structural clustering for single-cell RNA-seq data jointly through autoencoder and graph neural network.

Briefings in bioinformatics Mar 10, 2022
Single-cell RNA sequencing (scRNA-seq) permits researchers to study the complex mechanisms of cell heterogeneity and diversity. Unsupervised clustering is of central importance for the analysis of the scRNA-seq data, as it can be used to identify put...
Cluster Analysis Single-Cell Analysis RNA-Seq Sequence Analysis, RNA Neural Networks, Computer Gene Expression Profiling
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A deep learning framework for characterization of genotype data.

G3 (Bethesda, Md.) Mar 4, 2022
Dimensionality reduction is a data transformation technique widely used in various fields of genomics research. The application of dimensionality reduction to genotype data is known to capture genetic similarity between individuals, and is used for v...
Genome, Human Genotype Cluster Analysis Humans Computer Simulation Deep Learning Software
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Identification of cardiovascular high-risk groups from dynamic retinal vessel signals using untargeted machine learning.

Cardiovascular research Jan 29, 2022
AIMS: Dynamic retinal vessel analysis (DVA) provides a non-invasive way to assess microvascular function in patients and potentially to improve predictions of individual cardiovascular (CV) risk. The aim of our study was to use untargeted machine lea...
Workflow Light Vasodilation Cause of Death Signal Processing, Computer-Assisted Retinal Vessels Arterioles Venules Heart Disease Risk Factors Photic Stimulation Renal Dialysis Treatment Outcome Machine Learning Predictive Value of Tests Female Kidney Failure, Chronic Humans Cluster Analysis Cardiovascular Diseases Aged Middle Aged Male Risk Assessment
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SIGNET: single-cell RNA-seq-based gene regulatory network prediction using multiple-layer perceptron bagging.

Briefings in bioinformatics Jan 17, 2022
High-throughput single-cell RNA-seq data have provided unprecedented opportunities for deciphering the regulatory interactions among genes. However, such interactions are complex and often nonlinear or nonmonotonic, which makes their inference using ...
Cluster Analysis Gene Expression Regulation Algorithms Gene Expression Profiling Humans Gene Regulatory Networks Deep Learning Neural Networks, Computer Sequence Analysis, RNA Single-Cell Analysis Transcription Factors RNA-Seq
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Deep learning tackles single-cell analysis-a survey of deep learning for scRNA-seq analysis.

Briefings in bioinformatics Jan 17, 2022
Since its selection as the method of the year in 2013, single-cell technologies have become mature enough to provide answers to complex research questions. With the growth of single-cell profiling technologies, there has also been a significant incre...
Gene Expression Profiling Transcriptome Single-Cell Analysis RNA-Seq Deep Learning Humans Machine Learning Algorithms Sequence Analysis, RNA Cluster Analysis
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A comparison of deep learning-based pre-processing and clustering approaches for single-cell RNA sequencing data.

Briefings in bioinformatics Jan 17, 2022
The emergence of single cell RNA sequencing has facilitated the studied of genomes, transcriptomes and proteomes. As available single-cell RNA-seq datasets are released continuously, one of the major challenges facing traditional RNA analysis tools i...
Sequence Analysis, RNA Gene Expression Profiling Cluster Analysis Deep Learning Single-Cell Analysis
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Using Machine Learning to Improve Personalised Prediction: A Data-Driven Approach to Segment and Stratify Populations for Healthcare.

Studies in health technology and informatics Jan 14, 2022
Population Health Management typically relies on subjective decisions to segment and stratify populations. This study combines unsupervised clustering for segmentation and supervised classification, personalised to clusters, for stratification. An in...
Machine Learning Delivery of Health Care Unsupervised Machine Learning Cluster Analysis Predictive Value of Tests
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Deep neural learning based protein function prediction.

Mathematical biosciences and engineering : MBE Jan 7, 2022
It is vital for the annotation of uncharacterized proteins by protein function prediction. At present, Deep Neural Network based protein function prediction is mainly carried out for dataset of small scale proteins or Gene Ontology, and usually explo...
Cluster Analysis Neural Networks, Computer Proteins Algorithms Gene Ontology
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