AIMC Topic:
Cluster Analysis

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Phenotypic clustering of heart failure with preserved ejection fraction reveals different rates of hospitalization.

Journal of cardiovascular medicine (Hagerstown, Md.) Jan 1, 2021
AIMS: Approximately 50% of patients with heart failure have preserved (≥50%) ejection fraction (HFpEF). Improved understanding of the phenotypic heterogeneity of HFpEF might facilitate development of targeted therapies and interventions.
Humans Databases, Factual Prognosis Hospitalization Aged Aged, 80 and over Retrospective Studies Female Data Mining Administrative Claims, Healthcare Natural Language Processing Heart Failure Age Factors Stroke Volume Cluster Analysis Middle Aged Prevalence Male Comorbidity Ventricular Function, Left Time Factors United States
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Brain Tumor Segmentation of T1w MRI Images Based on Clustering Using Dimensionality Reduction Random Projection Technique.

Current medical imaging Jan 1, 2021
BACKGROUND: Early diagnosis of a brain tumor may increase life expectancy. Magnetic resonance imaging (MRI) accompanied by several segmentation algorithms is preferred as a reliable method for assessment. The availability of high-dimensional medical ...
Humans Magnetic Resonance Imaging Algorithms Fuzzy Logic Brain Neoplasms Cluster Analysis
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Semi-supervised audio-driven TV-news speaker diarization using deep neural embeddings.

The Journal of the Acoustical Society of America Dec 1, 2020
In this paper, an audio-driven, multimodal approach for speaker diarization in multimedia content is introduced and evaluated. The proposed algorithm is based on semi-supervised clustering of audio-visual embeddings, generated using deep learning tec...
Algorithms Cluster Analysis Neural Networks, Computer
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Detecting and Classifying Self-injurious Behavior in Autism Spectrum Disorder Using Machine Learning Techniques.

Journal of autism and developmental disorders Nov 1, 2020
Traditional self-injurious behavior (SIB) management can place compliance demands on the caregiver and have low ecological validity and accuracy. To support an SIB monitoring system for autism spectrum disorder (ASD), we evaluated machine learning me...
Child Electrocardiography Self-Injurious Behavior Cluster Analysis Adolescent Machine Learning Child, Preschool Autism Spectrum Disorder Female Humans Male
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A Systematic Evaluation of Interneuron Morphology Representations for Cell Type Discrimination.

Neuroinformatics Oct 1, 2020
Quantitative analysis of neuronal morphologies usually begins with choosing a particular feature representation in order to make individual morphologies amenable to standard statistics tools and machine learning algorithms. Many different feature rep...
Neuroimaging Interneurons Animals Machine Learning Mice Algorithms Cluster Analysis
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[Human activity recognition based on the inertial information and convolutional neural network].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi Aug 25, 2020
With the rapid improvement of the perception and computing capacity of mobile devices such as smart phones, human activity recognition using mobile devices as the carrier has been a new research hot-spot. The inertial information collected by the acc...
Neural Networks, Computer Algorithms Motion Human Activities Cluster Analysis Humans
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Machine learning and statistical methods for clustering single-cell RNA-sequencing data.

Briefings in bioinformatics Jul 15, 2020
UNLABELLED: Single-cell RNAsequencing (scRNA-seq) technologies have enabled the large-scale whole-transcriptome profiling of each individual single cell in a cell population. A core analysis of the scRNA-seq transcriptome profiles is to cluster the s...
Cluster Analysis Single-Cell Analysis Sequence Analysis, RNA Machine Learning Gene Expression Profiling
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Unsupervised stratification in neuroimaging through deep latent embeddings.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2020
There is growing evidence that the use of stringent and dichotomic diagnostic categories in many medical disciplines (particularly 'brain sciences' as neurology and psychiatry) is an oversimplification. Although clear diagnostic boundaries remain use...
Databases, Factual Brain Deep Learning Humans Connectome Cluster Analysis Neuroimaging
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Clinical Abbreviation Disambiguation Using Deep Contextualized Representation.

Studies in health technology and informatics Jun 16, 2020
The objective of this study is to develop a method for clinical abbreviation disambiguation using deep contextualized representation and cluster analysis. We employed the pre-trained BioELMo language model to generate the contextualized word vector f...
Algorithms Cluster Analysis Language Natural Language Processing
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Character-Level Neural Language Modelling in the Clinical Domain.

Studies in health technology and informatics Jun 16, 2020
Word embeddings have become the predominant representation scheme on a token-level for various clinical natural language processing (NLP) tasks. More recently, character-level neural language models, exploiting recurrent neural networks, have again r...
Semantics Neural Networks, Computer Language Natural Language Processing Patient Care Cluster Analysis
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