AI Medical Compendium Topic:
Cluster Analysis

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Application of fuzzy neural networks for modeling of biodegradation and biogas production in a full-scale internal circulation anaerobic reactor.

Journal of environmental science and health. Part A, Toxic/hazardous substances & environmental engineering
This paper presents the development and evaluation of three fuzzy neural network (FNN) models for a full-scale anaerobic digestion system treating paper-mill wastewater. The aim was the investigation of feasibility of the approach-based control syste...

Clustering-based classification of road traffic accidents using hierarchical clustering and artificial neural networks.

International journal of injury control and safety promotion
Artificial neural networks (ANNs) have been widely used in predicting the severity of road traffic crashes. All available information about previously occurred accidents is typically used for building a single prediction model (i.e., classifier). Too...

An Incremental Radial Basis Function Network Based on Information Granules and Its Application.

Computational intelligence and neuroscience
This paper is concerned with the design of an Incremental Radial Basis Function Network (IRBFN) by combining Linear Regression (LR) and local RBFN for the prediction of heating load and cooling load in residential buildings. Here the proposed IRBFN i...

Automated learning of domain taxonomies from text using background knowledge.

Journal of biomedical informatics
In this paper, we present an automated method for taxonomy learning, focusing on concept formation and hierarchical relation learning. To infer such relations, we partition the extracted concepts and group them into closely-related clusters using Hie...

Unsupervised class labeling of diffuse lung diseases using frequent attribute patterns.

International journal of computer assisted radiology and surgery
PURPOSE: For realizing computer-aided diagnosis (CAD) of computed tomography (CT) images, many pattern recognition methods have been applied to automatic classification of normal and abnormal opacities; however, for the learning of accurate classifie...

Classification of breast cancer patients using somatic mutation profiles and machine learning approaches.

BMC systems biology
BACKGROUND: The high degree of heterogeneity observed in breast cancers makes it very difficult to classify the cancer patients into distinct clinical subgroups and consequently limits the ability to devise effective therapeutic strategies. Several c...

Clustering of soybean genotypes via Ward-MLM and ANNs associated with mixed models.

Genetics and molecular research : GMR
The objectives of this study were to use mixed models to confirm the presence of genetic variability in 16 soybean genotypes, to compare clusters generated by artificial neural networks (ANNs) with those created by the Ward modified location model (M...

Global cluster synchronization in nonlinearly coupled community networks with heterogeneous coupling delays.

Neural networks : the official journal of the International Neural Network Society
This investigation establishes the global cluster synchronization of complex networks with a community structure based on an iterative approach. The units comprising the network are described by differential equations, and can be non-autonomous and i...

ADMET Evaluation in Drug Discovery. 16. Predicting hERG Blockers by Combining Multiple Pharmacophores and Machine Learning Approaches.

Molecular pharmaceutics
Blockade of human ether-à-go-go related gene (hERG) channel by compounds may lead to drug-induced QT prolongation, arrhythmia, and Torsades de Pointes (TdP), and therefore reliable prediction of hERG liability in the early stages of drug design is qu...

A new thresholding technique based on fuzzy set as an application to leukocyte nucleus segmentation.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: The main aim of this paper is to segment leukocytes in blood smear images using interval-valued intuitionistic fuzzy sets (IVIFSs). Generally, uncertainties occur in terms of vagueness through brightness levels of image. Pr...