AIMC Topic: Cluster Analysis

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Dual vigilance fuzzy adaptive resonance theory.

Neural networks : the official journal of the International Neural Network Society
Clusters retrieved by generic Adaptive Resonance Theory (ART) networks are limited to their internal categorical representation. This study extends the capabilities of ART by incorporating multiple vigilance thresholds in a single network: stricter (...

Automatic lung nodule detection using a 3D deep convolutional neural network combined with a multi-scale prediction strategy in chest CTs.

Computers in biology and medicine
OBJECTIVE: A novel computer-aided detection (CAD) scheme for lung nodule detection using a 3D deep convolutional neural network combined with a multi-scale prediction strategy is proposed to assist radiologists by providing a second opinion on accura...

Potential identification of vitamin B6 responsiveness in autism spectrum disorder utilizing phenotype variables and machine learning methods.

Scientific reports
We investigated whether machine learning methods could potentially identify a subgroup of persons with autism spectrum disorder (ASD) who show vitamin B6 responsiveness by selected phenotype variables. We analyzed the existing data from our intervent...

Laplacian mixture modeling for network analysis and unsupervised learning on graphs.

PloS one
Laplacian mixture models identify overlapping regions of influence in unlabeled graph and network data in a scalable and computationally efficient way, yielding useful low-dimensional representations. By combining Laplacian eigenspace and finite mixt...

Predicting of anaphylaxis in big data EMR by exploring machine learning approaches.

Journal of biomedical informatics
Anaphylaxis is a life-threatening allergic reaction that occurs suddenly after contact with an allergen. Epidemiological studies about anaphylaxis are very important in planning and evaluating new strategies that prevent this reaction, but also in pr...

Learning zero-cost portfolio selection with pattern matching.

PloS one
We replicate and extend the adversarial expert based learning approach of Györfi et al to the situation of zero-cost portfolio selection implemented with a quadratic approximation derived from the mutual fund separation theorems. The algorithm is app...

A robust data-driven approach identifies four personality types across four large data sets.

Nature human behaviour
Understanding human personality has been a focus for philosophers and scientists for millennia. It is now widely accepted that there are about five major personality domains that describe the personality profile of an individual. In contrast to perso...

Data mining and machine learning approaches for the integration of genome-wide association and methylation data: methodology and main conclusions from GAW20.

BMC genetics
BACKGROUND: Multiple layers of genetic and epigenetic variability are being simultaneously explored in an increasing number of health studies. We summarize here different approaches applied in the Data Mining and Machine Learning group at the GAW20 t...

Bounded Fuzzy Possibilistic Method Reveals Information about Lung Cancer through Analysis of Metabolomics.

IEEE/ACM transactions on computational biology and bioinformatics
Learning methods, such as conventional clustering and classification, have been applied in diagnosing diseases to categorize samples based on their features. Going beyond clustering samples, membership degrees represent to what degree each sample bel...

Novel symmetry-based gene-gene dissimilarity measures utilizing Gene Ontology: Application in gene clustering.

Gene
In recent years DNA microarray technology, leading to the generation of high-volume biological data, has gained significant attention. To analyze this high volume gene-expression data, one such powerful tool is Clustering. For any clustering algorith...