AI Medical Compendium Topic:
Cluster Analysis

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Low-rank representation with adaptive graph regularization.

Neural networks : the official journal of the International Neural Network Society
Low-rank representation (LRR) has aroused much attention in the community of data mining. However, it has the following twoproblems which greatly limit its applications: (1) it cannot discover the intrinsic structure of data owing to the neglect of t...

Deep Neural Networks for In Situ Hybridization Grid Completion and Clustering.

IEEE/ACM transactions on computational biology and bioinformatics
Transcriptome in brain plays a crucial role in understanding the cortical organization and the development of brain structure and function. Two challenges, incomplete data and high dimensionality of transcriptome, remain unsolved. Here, we present a ...

Fuzzy c-means-based architecture reduction of a probabilistic neural network.

Neural networks : the official journal of the International Neural Network Society
The efficiency of the probabilistic neural network (PNN) is very sensitive to the cardinality of a considered input data set. It results from the design of the network's pattern layer. In this layer, the neurons perform an activation on all input rec...

RETRACTED: Diagnosis labeling with disease-specific characteristics mining.

Artificial intelligence in medicine
This article has been retracted: please see Elsevier Policy on Article Withdrawal (https://www.elsevier.com/about/our-business/policies/article-withdrawal). This article has been retracted at the request of the authors; serious errors had been introd...

Prioritising references for systematic reviews with RobotAnalyst: A user study.

Research synthesis methods
Screening references is a time-consuming step necessary for systematic reviews and guideline development. Previous studies have shown that human effort can be reduced by using machine learning software to prioritise large reference collections such t...

An unsupervised machine learning method for discovering patient clusters based on genetic signatures.

Journal of biomedical informatics
INTRODUCTION: Many chronic disorders have genomic etiology, disease progression, clinical presentation, and response to treatment that vary on a patient-to-patient basis. Such variability creates a need to identify characteristics within patient popu...

Mining features for biomedical data using clustering tree ensembles.

Journal of biomedical informatics
The volume of biomedical data available to the machine learning community grows very rapidly. A rational question is how informative these data really are or how discriminant the features describing the data instances are. Several biomedical datasets...

Distribution based Fuzzy Estimate Spectral Clustering for Cancer Detection with Protein Sequence and Structural Motifs.

Asian Pacific journal of cancer prevention : APJCP
Objective: In biological data analysis, protein sequence and structural motifs are an amino-acid sequence patterns that are widespread and used as tools for detecting the cancer at an earlier stage. To improve the cancer detection with minimum space ...

A machine-learned analysis of human gene polymorphisms modulating persisting pain points to major roles of neuroimmune processes.

European journal of pain (London, England)
BACKGROUND: Human genetic research has implicated functional variants of more than one hundred genes in the modulation of persisting pain. Artificial intelligence and machine-learning techniques may combine this knowledge with results of genetic rese...

Environmental properties of cells improve machine learning-based phenotype recognition accuracy.

Scientific reports
To answer major questions of cell biology, it is often essential to understand the complex phenotypic composition of cellular systems precisely. Modern automated microscopes produce vast amounts of images routinely, making manual analysis nearly impo...