AI Medical Compendium Topic:
Unsupervised Machine Learning

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Unsupervised delineation of stratum corneum using reflectance confocal microscopy and spectral clustering.

Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI)
BACKGROUND: Measuring the thickness of the stratum corneum (SC) in vivo is often required in pharmacological, dermatological, and cosmetological studies. Reflectance confocal microscopy (RCM) offers a non-invasive imaging-based approach. However, RCM...

Unsupervised neural spike sorting for high-density microelectrode arrays with convolutive independent component analysis.

Journal of neuroscience methods
BACKGROUND: Unsupervised identification of action potentials in multi-channel extracellular recordings, in particular from high-density microelectrode arrays with thousands of sensors, is an unresolved problem. While independent component analysis (I...

Characterization of myocardial motion patterns by unsupervised multiple kernel learning.

Medical image analysis
We propose an independent objective method to characterize different patterns of functional responses to stress in the heart failure with preserved ejection fraction (HFPEF) syndrome by combining multiple temporally-aligned myocardial velocity traces...

Joint feature-sample selection and robust diagnosis of Parkinson's disease from MRI data.

NeuroImage
Parkinson's disease (PD) is an overwhelming neurodegenerative disorder caused by deterioration of a neurotransmitter, known as dopamine. Lack of this chemical messenger impairs several brain regions and yields various motor and non-motor symptoms. In...

A segmentation and classification scheme for single tooth in MicroCT images based on 3D level set and k-means+.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Accurate classification of different anatomical structures of teeth from medical images provides crucial information for the stress analysis in dentistry. Usually, the anatomical structures of teeth are manually labeled by experienced clinical doctor...

Filtering large-scale event collections using a combination of supervised and unsupervised learning for event trigger classification.

Journal of biomedical semantics
BACKGROUND: Biomedical event extraction is one of the key tasks in biomedical text mining, supporting various applications such as database curation and hypothesis generation. Several systems, some of which have been applied at a large scale, have be...

A hierarchical model for integrating unsupervised generative embedding and empirical Bayes.

Journal of neuroscience methods
BACKGROUND: Generative models of neuroimaging data, such as dynamic causal models (DCMs), are commonly used for inferring effective connectivity from individual subject data. Recently introduced "generative embedding" approaches have used DCM-based c...

Chemical named entity recognition in patents by domain knowledge and unsupervised feature learning.

Database : the journal of biological databases and curation
Medicinal chemistry patents contain rich information about chemical compounds. Although much effort has been devoted to extracting chemical entities from scientific literature, limited numbers of patent mining systems are publically available, probab...

Learning Topologies with the Growing Neural Forest.

International journal of neural systems
In this work, a novel self-organizing model called growing neural forest (GNF) is presented. It is based on the growing neural gas (GNG), which learns a general graph with no special provisions for datasets with separated clusters. On the contrary, t...