AIMC Topic: Cluster Analysis

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Retinal blood vessel extraction employing effective image features and combination of supervised and unsupervised machine learning methods.

Artificial intelligence in medicine
In medicine, retinal vessel analysis of fundus images is a prominent task for the screening and diagnosis of various ophthalmological and cardiovascular diseases. In this research, a method is proposed for extracting the retinal blood vessels employi...

Model-based hearing diagnostics based on wideband tympanometry measurements utilizing fuzzy arithmetic.

Hearing research
Today's audiometric methods for the diagnosis of middle ear disease are often based on a comparison of measurements with standard curves, that represent the statistical range of normal hearing responses. Because of large inter-individual variances in...

Simultaneous spatiotemporal tracking and oxygen sensing of transient implants in vivo using hot-spot MRI and machine learning.

Proceedings of the National Academy of Sciences of the United States of America
A varying oxygen environment is known to affect cellular function in disease as well as activity of various therapeutics. For transient structures, whether they are unconstrained therapeutic transplants, migrating cells during tumor metastasis, or ce...

Unsupervised Learning Approach for Comparing Multiple Transposon Insertion Sequencing Studies.

mSphere
Transposon insertion sequencing (TIS) is a widely used technique for conducting genome-scale forward genetic screens in bacteria. However, few methods enable comparison of TIS data across multiple replicates of a screen or across independent screens,...

Rehab-Net: Deep Learning Framework for Arm Movement Classification Using Wearable Sensors for Stroke Rehabilitation.

IEEE transactions on bio-medical engineering
In this paper, we present a deep learning framework "Rehab-Net" for effectively classifying three upper limb movements of the human arm, involving extension, flexion, and rotation of the forearm, which, over the time, could provide a measure of rehab...

CirGO: an alternative circular way of visualising gene ontology terms.

BMC bioinformatics
BACKGROUND: Prioritisation of gene ontology terms from differential gene expression analyses in a two-dimensional format remains a challenge with exponentially growing data volumes. Typically, gene ontology terms are represented as tree-maps that enc...

Support vector machine with quantile hyper-spheres for pattern classification.

PloS one
This paper formulates a support vector machine with quantile hyper-spheres (QHSVM) for pattern classification. The idea of QHSVM is to build two quantile hyper-spheres with the same center for positive or negative training samples. Every quantile hyp...

Application of adaptive-network-based fuzzy inference systems to the parameter optimization of a biochemical rule-based model.

Computers in biology and medicine
In this study, the binding of allergens to antibody-receptor complexes was investigated. This process is important in understanding the allergic response. A BioNetGen model that simulates this process, combined with a novel method for encoding steric...

Deep divergence-based approach to clustering.

Neural networks : the official journal of the International Neural Network Society
A promising direction in deep learning research consists in learning representations and simultaneously discovering cluster structure in unlabeled data by optimizing a discriminative loss function. As opposed to supervised deep learning, this line of...

Finite-time cluster synchronization for a class of fuzzy cellular neural networks via non-chattering quantized controllers.

Neural networks : the official journal of the International Neural Network Society
This paper considers the finite-time cluster synchronization (FTCS) of coupled fuzzy cellular neural networks (FCNNs) with Markovian switching topology, discontinuous activation functions, proportional leakage, and time-varying unbounded delays. Nove...