AI Medical Compendium Topic:
Cluster Analysis

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Discriminative clustering on manifold for adaptive transductive classification.

Neural networks : the official journal of the International Neural Network Society
In this paper, we mainly propose a novel adaptive transductive label propagation approach by joint discriminative clustering on manifolds for representing and classifying high-dimensional data. Our framework seamlessly combines the unsupervised manif...

Bias-Free Chemically Diverse Test Sets from Machine Learning.

ACS combinatorial science
Current benchmarking methods in quantum chemistry rely on databases that are built using a chemist's intuition. It is not fully understood how diverse or representative these databases truly are. Multivariate statistical techniques like archetypal an...

Clustering and Candidate Motif Detection in Exosomal miRNAs by Application of Machine Learning Algorithms.

Interdisciplinary sciences, computational life sciences
BACKGROUND: The clustering pattern and motifs give immense information about any biological data. An application of machine learning algorithms for clustering and candidate motif detection in miRNAs derived from exosomes is depicted in this paper. Re...

Effects of additional data on Bayesian clustering.

Neural networks : the official journal of the International Neural Network Society
Hierarchical probabilistic models, such as mixture models, are used for cluster analysis. These models have two types of variables: observable and latent. In cluster analysis, the latent variable is estimated, and it is expected that additional infor...

Differentiating Thamnocalamus Munro from Fargesia Franchet emend. Yi (Bambusoideae, Poaceae): novel evidence from morphological and neural-network analyses.

Scientific reports
Fargesia Franchet emend. Yi is closely allied with Thamnocalamus Munro but differs in many major morphological characteristics. Based on traditional morphological characters, it is difficult to differentiate these two genera. The current study measur...

Recommender system based on scarce information mining.

Neural networks : the official journal of the International Neural Network Society
Guessing what user may like is now a typical interface for video recommendation. Nowadays, the highly popular user generated content sites provide various sources of information such as tags for recommendation tasks. Motivated by a real world online ...

Classification of Paediatric Inflammatory Bowel Disease using Machine Learning.

Scientific reports
Paediatric inflammatory bowel disease (PIBD), comprising Crohn's disease (CD), ulcerative colitis (UC) and inflammatory bowel disease unclassified (IBDU) is a complex and multifactorial condition with increasing incidence. An accurate diagnosis of PI...

NFPscanner: a webtool for knowledge-based deciphering of biomedical networks.

BMC bioinformatics
BACKGROUND: Many biological pathways have been created to represent different types of knowledge, such as genetic interactions, metabolic reactions, and gene-regulating and physical-binding relationships. Biologists are using a wide range of omics da...

Semi-supervised medical entity recognition: A study on Spanish and Swedish clinical corpora.

Journal of biomedical informatics
OBJECTIVE: The goal of this study is to investigate entity recognition within Electronic Health Records (EHRs) focusing on Spanish and Swedish. Of particular importance is a robust representation of the entities. In our case, we utilized unsupervised...

Unsupervised Machine Learning for Developing Personalised Behaviour Models Using Activity Data.

Sensors (Basel, Switzerland)
The goal of this study is to address two major issues that undermine the large scale deployment of smart home sensing solutions in people's homes. These include the costs associated with having to install and maintain a large number of sensors, and t...