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Cluster Analysis

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Clinically Distinct Subtypes of Acute Kidney Injury on Hospital Admission Identified by Machine Learning Consensus Clustering.

Medical sciences (Basel, Switzerland)
BACKGROUND: We aimed to cluster patients with acute kidney injury at hospital admission into clinically distinct subtypes using an unsupervised machine learning approach and assess the mortality risk among the distinct clusters.

Unsupervised Machine Learning Applied to Seismic Interpretation: Towards an Unsupervised Automated Interpretation Tool.

Sensors (Basel, Switzerland)
Seismic interpretation is a fundamental process for hydrocarbon exploration. This activity comprises identifying geological information through the processing and analysis of seismic data represented by different attributes. The interpretation proces...

Incorporating metadata in HIV transmission network reconstruction: A machine learning feasibility assessment.

PLoS computational biology
HIV molecular epidemiology estimates the transmission patterns from clustering genetically similar viruses. The process involves connecting genetically similar genotyped viral sequences in the network implying epidemiological transmissions. This tech...

Combining Supervised and Unsupervised Learning Algorithms for Human Activity Recognition.

Sensors (Basel, Switzerland)
Human activity recognition is an extensively researched topic in the last decade. Recent methods employ supervised and unsupervised deep learning techniques in which spatial and temporal dependency is modeled. This paper proposes a novel approach for...

Identifying homogeneous subgroups of patients and important features: a topological machine learning approach.

BMC bioinformatics
BACKGROUND: This paper exploits recent developments in topological data analysis to present a pipeline for clustering based on Mapper, an algorithm that reduces complex data into a one-dimensional graph.

Automated assignment of cell identity from single-cell multiplexed imaging and proteomic data.

Cell systems
A major challenge in the analysis of highly multiplexed imaging data is the assignment of cells to a priori known cell types. Existing approaches typically solve this by clustering cells followed by manual annotation. However, these often require sev...

Evaluation of Teachers' Educational Technology Ability Based on Fuzzy Clustering Generalized Regression Neural Network.

Computational intelligence and neuroscience
The improvement of teachers' educational technology ability is one of the main methods to improve the management efficiency of colleges and universities in China, and the scientific evaluation of teachers' ability is of great significance. In view of...

Subgroup Preference Neural Network.

Sensors (Basel, Switzerland)
Subgroup label ranking aims to rank groups of labels using a single ranking model, is a new problem faced in preference learning. This paper introduces the Subgroup Preference Neural Network () that combines multiple networks have different activatio...

Upper-Limb Motion Recognition Based on Hybrid Feature Selection: Algorithm Development and Validation.

JMIR mHealth and uHealth
BACKGROUND: For rehabilitation training systems, it is essential to automatically record and recognize exercises, especially when more than one type of exercise is performed without a predefined sequence. Most motion recognition methods are based on ...

Multi-feature data repository development and analytics for image cosegmentation in high-throughput plant phenotyping.

PloS one
Cosegmentation is a newly emerging computer vision technique used to segment an object from the background by processing multiple images at the same time. Traditional plant phenotyping analysis uses thresholding segmentation methods which result in h...