AI Medical Compendium Topic:
Cluster Analysis

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Classifying GABAergic interneurons with semi-supervised projected model-based clustering.

Artificial intelligence in medicine
OBJECTIVES: A recently introduced pragmatic scheme promises to be a useful catalog of interneuron names. We sought to automatically classify digitally reconstructed interneuronal morphologies according to this scheme. Simultaneously, we sought to dis...

Learning-regulated context relevant topographical map.

IEEE transactions on neural networks and learning systems
Kohonen's self-organizing map (SOM) is used to map high-dimensional data into a low-dimensional representation (typically a 2-D or 3-D space) while preserving their topological characteristics. A major reason for its application is to be able to visu...

Classification of lung cancer using ensemble-based feature selection and machine learning methods.

Molecular bioSystems
Lung cancer is one of the leading causes of death worldwide. There are three major types of lung cancers, non-small cell lung cancer (NSCLC), small cell lung cancer (SCLC) and carcinoid. NSCLC is further classified into lung adenocarcinoma (LADC), sq...

Identifying predictive features in drug response using machine learning: opportunities and challenges.

Annual review of pharmacology and toxicology
This article reviews several techniques from machine learning that can be used to study the problem of identifying a small number of features, from among tens of thousands of measured features, that can accurately predict a drug response. Prediction ...

Active learning for semi-supervised clustering based on locally linear propagation reconstruction.

Neural networks : the official journal of the International Neural Network Society
The success of semi-supervised clustering relies on the effectiveness of side information. To get effective side information, a new active learner learning pairwise constraints known as must-link and cannot-link constraints is proposed in this paper....

Molecular classification of amyotrophic lateral sclerosis by unsupervised clustering of gene expression in motor cortex.

Neurobiology of disease
Amyotrophic lateral sclerosis (ALS) is a rapidly progressive and ultimately fatal neurodegenerative disease, caused by the loss of motor neurons in the brain and spinal cord. Although 10% of ALS cases are familial (FALS), the majority are sporadic (S...

A vector reconstruction based clustering algorithm particularly for large-scale text collection.

Neural networks : the official journal of the International Neural Network Society
Along with the fast evolvement of internet technology, internet users have to face the large amount of textual data every day. Apparently, organizing texts into categories can help users dig the useful information from large-scale text collection. Cl...

Convex nonnegative matrix factorization with manifold regularization.

Neural networks : the official journal of the International Neural Network Society
Nonnegative Matrix Factorization (NMF) has been extensively applied in many areas, including computer vision, pattern recognition, text mining, and signal processing. However, nonnegative entries are usually required for the data matrix in NMF, which...

Approximate kernel competitive learning.

Neural networks : the official journal of the International Neural Network Society
Kernel competitive learning has been successfully used to achieve robust clustering. However, kernel competitive learning (KCL) is not scalable for large scale data processing, because (1) it has to calculate and store the full kernel matrix that is ...

Aggregator: a machine learning approach to identifying MEDLINE articles that derive from the same underlying clinical trial.

Methods (San Diego, Calif.)
OBJECTIVE: It is important to identify separate publications that report outcomes from the same underlying clinical trial, in order to avoid over-counting these as independent pieces of evidence.