AI Medical Compendium Topic:
Cluster Analysis

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Multimodal Data Analysis of Alzheimer's Disease Based on Clustering Evolutionary Random Forest.

IEEE journal of biomedical and health informatics
Alzheimer's disease (AD) has become a severe medical challenge. Advances in technologies produced high-dimensional data of different modalities including functional magnetic resonance imaging (fMRI) and single nucleotide polymorphism (SNP). Understan...

Machine-learned identification of psychological subgroups with relation to pain interference in patients after breast cancer treatments.

Breast (Edinburgh, Scotland)
BACKGROUND: Persistent pain in breast cancer survivors is common. Psychological and sleep-related factors modulate perception, interpretation and coping with pain and may contribute to the clinical phenotype. The present analysis pursued the hypothes...

Drug-target interaction prediction with tree-ensemble learning and output space reconstruction.

BMC bioinformatics
BACKGROUND: Computational prediction of drug-target interactions (DTI) is vital for drug discovery. The experimental identification of interactions between drugs and target proteins is very onerous. Modern technologies have mitigated the problem, lev...

Machine learning-based prediction of glioma margin from 5-ALA induced PpIX fluorescence spectroscopy.

Scientific reports
Gliomas are infiltrative brain tumors with a margin difficult to identify. 5-ALA induced PpIX fluorescence measurements are a clinical standard, but expert-based classification models still lack sensitivity and specificity. Here a fully automatic clu...

Blind method for discovering number of clusters in multidimensional datasets by regression on linkage hierarchies generated from random data.

PloS one
Determining intrinsic number of clusters in a multidimensional dataset is a commonly encountered problem in exploratory data analysis. Unsupervised clustering algorithms often rely on specification of cluster number as an input parameter. However, th...

Automatic classification of gait patterns in children with cerebral palsy using fuzzy clustering method.

Clinical biomechanics (Bristol, Avon)
BACKGROUND: Subjective classification of gait pattern in children with cerebral palsy depends on the assessor's experience, while mathematical methods produce virtual groups with no clinical interpretation.

Using transfer learning from prior reference knowledge to improve the clustering of single-cell RNA-Seq data.

Scientific reports
In many research areas scientists are interested in clustering objects within small datasets while making use of prior knowledge from large reference datasets. We propose a method to apply the machine learning concept of transfer learning to unsuperv...

Machine Learning Characterization of COPD Subtypes: Insights From the COPDGene Study.

Chest
COPD is a heterogeneous syndrome. Many COPD subtypes have been proposed, but there is not yet consensus on how many COPD subtypes there are and how they should be defined. The COPD Genetic Epidemiology Study (COPDGene), which has generated 10-year lo...

Synchronization of Hindmarsh Rose Neurons.

Neural networks : the official journal of the International Neural Network Society
Modeling and implementation of biological neurons are key to the fundamental understanding of neural network architectures in the brain and its cognitive behavior. Synchronization of neuronal models play a significant role in neural signal processing...

A Machine Learning-Based Raman Spectroscopic Assay for the Identification of and Related Species.

Molecules (Basel, Switzerland)
, the causative agent of glanders, and , the causative agent of melioidosis in humans and animals, are genetically closely related. The high infectious potential of both organisms, their serological cross-reactivity, and similar clinical symptoms in ...