AI Medical Compendium Topic:
Cluster Analysis

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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...

A Novel Extension to Fuzzy Connectivity for Body Composition Analysis: Applications in Thigh, Brain, and Whole Body Tissue Segmentation.

IEEE transactions on bio-medical engineering
Magnetic resonance imaging (MRI) is the non-invasive modality of choice for body tissue composition analysis due to its excellent soft-tissue contrast and lack of ionizing radiation. However, quantification of body composition requires an accurate se...

Sequential Integration of Fuzzy Clustering and Expectation Maximization for Transcription Factor Binding Site Identification.

Journal of computational biology : a journal of computational molecular cell biology
The identification of transcription factor binding sites (TFBSs) is a problem for which computational methods offer great hope. Thus far, the expectation maximization (EM) technique has been successfully utilized in finding TFBSs in DNA sequences, bu...

Solution to travelling salesman problem by clusters and a modified multi-restart iterated local search metaheuristic.

PloS one
This article finds feasible solutions to the travelling salesman problem, obtaining the route with the shortest distance to visit n cities just once, returning to the starting city. The problem addressed is clustering the cities, then using the NEH h...

A convolutional route to abbreviation disambiguation in clinical text.

Journal of biomedical informatics
OBJECTIVE: Abbreviations sense disambiguation is a special case of word sense disambiguation. Machine learning methods based on neural networks showed promising results for word sense disambiguation (Festag and Spreckelsen, 2017) [1] and, here we ass...