AI Medical Compendium Topic:
Cluster Analysis

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A new modeling approach for quantifying expert opinion in the drug discovery process.

Statistics in medicine
Expert opinion plays an important role when choosing clusters of chemical compounds for further investigation. Often, the process by which the clusters are assigned to the experts for evaluation, the so-called selection process, and the qualitative r...

Neurons from the adult human dentate nucleus: neural networks in the neuron classification.

Journal of theoretical biology
OBJECTIVES: Topological (central vs. border neuron type) and morphological classification of adult human dentate nucleus neurons according to their quantified histomorphological properties using neural networks on real and virtual neuron samples.

The ligand binding mechanism to purine nucleoside phosphorylase elucidated via molecular dynamics and machine learning.

Nature communications
The study of biomolecular interactions between a drug and its biological target is of paramount importance for the design of novel bioactive compounds. In this paper, we report on the use of molecular dynamics (MD) simulations and machine learning to...

A New Multivariate Approach for Prognostics Based on Extreme Learning Machine and Fuzzy Clustering.

IEEE transactions on cybernetics
Prognostics is a core process of prognostics and health management (PHM) discipline, that estimates the remaining useful life (RUL) of a degrading machinery to optimize its service delivery potential. However, machinery operates in a dynamic environm...

Self-adaptive prediction of cloud resource demands using ensemble model and subtractive-fuzzy clustering based fuzzy neural network.

Computational intelligence and neuroscience
In IaaS (infrastructure as a service) cloud environment, users are provisioned with virtual machines (VMs). To allocate resources for users dynamically and effectively, accurate resource demands predicting is essential. For this purpose, this paper p...

Learning machines and sleeping brains: Automatic sleep stage classification using decision-tree multi-class support vector machines.

Journal of neuroscience methods
BACKGROUND: Sleep staging is a critical step in a range of electrophysiological signal processing pipelines used in clinical routine as well as in sleep research. Although the results currently achievable with automatic sleep staging methods are prom...

Fast traffic sign recognition with a rotation invariant binary pattern based feature.

Sensors (Basel, Switzerland)
Robust and fast traffic sign recognition is very important but difficult for safe driving assistance systems. This study addresses fast and robust traffic sign recognition to enhance driving safety. The proposed method includes three stages. First, a...

Artificial Bee Colony Algorithm Based on Information Learning.

IEEE transactions on cybernetics
Inspired by the fact that the division of labor and cooperation play extremely important roles in the human history development, this paper develops a novel artificial bee colony algorithm based on information learning (ILABC, for short). In ILABC, a...

Development of a novel fingerprint for chemical reactions and its application to large-scale reaction classification and similarity.

Journal of chemical information and modeling
Fingerprint methods applied to molecules have proven to be useful for similarity determination and as inputs to machine-learning models. Here, we present the development of a new fingerprint for chemical reactions and validate its usefulness in build...

Enhanced low-rank representation via sparse manifold adaption for semi-supervised learning.

Neural networks : the official journal of the International Neural Network Society
Constructing an informative and discriminative graph plays an important role in various pattern recognition tasks such as clustering and classification. Among the existing graph-based learning models, low-rank representation (LRR) is a very competiti...