AI Medical Compendium Topic:
Cluster Analysis

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Multilayer bootstrap networks.

Neural networks : the official journal of the International Neural Network Society
Multilayer bootstrap network builds a gradually narrowed multilayer nonlinear network from bottom up for unsupervised nonlinear dimensionality reduction. Each layer of the network is a nonparametric density estimator. It consists of a group of k-cent...

Bayesian estimation of multidimensional latent variables and its asymptotic accuracy.

Neural networks : the official journal of the International Neural Network Society
Hierarchical learning models, such as mixture models and Bayesian networks, are widely employed for unsupervised learning tasks, such as clustering analysis. They consist of observable and latent variables, which represent the given data and their un...

Molecular identification and in vitro antifungal susceptibility of Scedosporium complex isolates from high-human-activity sites in Mexico.

Mycologia
The genus Scedosporium is a complex of ubiquitous moulds associated with a wide spectrum of clinical entities, with high mortality principally in immunocompromised hosts. Ecology of these microorganisms has been studied performing isolations from env...

Possible world based consistency learning model for clustering and classifying uncertain data.

Neural networks : the official journal of the International Neural Network Society
Possible world has shown to be effective for handling various types of data uncertainty in uncertain data management. However, few uncertain data clustering and classification algorithms are proposed based on possible world. Moreover, existing possib...

Clustering fMRI data with a robust unsupervised learning algorithm for neuroscience data mining.

Journal of neuroscience methods
BACKGROUND: Clustering approaches used in functional magnetic resonance imaging (fMRI) research use brain activity to divide the brain into various parcels with some degree of homogeneous characteristics, but choosing the appropriate clustering algor...

Mortality prediction in intensive care units (ICUs) using a deep rule-based fuzzy classifier.

Journal of biomedical informatics
Electronic health records (EHRs) contain critical information useful for clinical studies. Early assessment of patients' mortality in intensive care units is of great importance. In this paper, a Deep Rule-Based Fuzzy System (DRBFS) was proposed to d...

Cell Segmentation Based on FOPSO Combined With Shape Information Improved Intuitionistic FCM.

IEEE journal of biomedical and health informatics
Fuzzy c-means (FCM) clustering algorithms have been proved to be effective image segmentation techniques. However, FCM clustering algorithms are sensitive to noises and initialization. They cannot effectively segment cell images with inhomogeneous gr...

Psoriasis skin biopsy image segmentation using Deep Convolutional Neural Network.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Development of machine assisted tools for automatic analysis of psoriasis skin biopsy image plays an important role in clinical assistance. Development of automatic approach for accurate segmentation of psoriasis skin biopsy...

Prediction of soil urea conversion and quantification of the importance degrees of influencing factors through a new combinatorial model based on cluster method and artificial neural network.

Chemosphere
Quantitative prediction of soil urea conversion is crucial in determining the mechanism of nitrogen transformation and understanding the dynamics of soil nutrients. This study aimed to establish a combinatorial prediction model (MCA-F-ANN) for soil u...