AI Medical Compendium Topic:
Cluster Analysis

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Development of a sugar-binding residue prediction system from protein sequences using support vector machine.

Computational biology and chemistry
Several methods have been proposed for protein-sugar binding site prediction using machine learning algorithms. However, they are not effective to learn various properties of binding site residues caused by various interactions between proteins and s...

A recurrence model for laryngeal cancer based on SVM and gene function clustering.

Acta oto-laryngologica
CONCLUSION: A prognostic model was obtained for LC. Several critical genes were unveiled. They could be potentially applied for LC recurrence prediction.

Why so GLUMM? Detecting depression clusters through graphing lifestyle-environs using machine-learning methods (GLUMM).

European psychiatry : the journal of the Association of European Psychiatrists
BACKGROUND: Key lifestyle-environ risk factors are operative for depression, but it is unclear how risk factors cluster. Machine-learning (ML) algorithms exist that learn, extract, identify and map underlying patterns to identify groupings of depress...

Machine-learned pattern identification in olfactory subtest results.

Scientific reports
The human sense of smell is often analyzed as being composed of three main components comprising olfactory threshold, odor discrimination and the ability to identify odors. A relevant distinction of the three components and their differential changes...

Human Motion Retrieval Based on Statistical Learning and Bayesian Fusion.

PloS one
A novel motion retrieval approach based on statistical learning and Bayesian fusion is presented. The approach includes two primary stages. (1) In the learning stage, fuzzy clustering is utilized firstly to get the representative frames of motions, a...

Inferring Unknown Biological Function by Integration of GO Annotations and Gene Expression Data.

IEEE/ACM transactions on computational biology and bioinformatics
Characterizing genes with semantic information is an important process regarding the description of gene products. In spite that complete genomes of many organisms have been already sequenced, the biological functions of all of their genes are still ...

ChemDataExtractor: A Toolkit for Automated Extraction of Chemical Information from the Scientific Literature.

Journal of chemical information and modeling
The emergence of "big data" initiatives has led to the need for tools that can automatically extract valuable chemical information from large volumes of unstructured data, such as the scientific literature. Since chemical information can be present i...

Successful classification of cocaine dependence using brain imaging: a generalizable machine learning approach.

BMC bioinformatics
BACKGROUND: Neuroimaging studies have yielded significant advances in the understanding of neural processes relevant to the development and persistence of addiction. However, these advances have not explored extensively for diagnostic accuracy in hum...

Brief isoflurane anaesthesia affects differential gene expression, gene ontology and gene networks in rat brain.

Behavioural brain research
Much is still unknown about the mechanisms of effects of even brief anaesthesia on the brain and previous studies have simply compared differential expression profiles with and without anaesthesia. We hypothesised that network analysis, in addition t...

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...