AIMC Topic:
Supervised Machine Learning

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A k-mer-based barcode DNA classification methodology based on spectral representation and a neural gas network.

Artificial intelligence in medicine Jul 4, 2015
OBJECTIVES: In this paper, an alignment-free method for DNA barcode classification that is based on both a spectral representation and a neural gas network for unsupervised clustering is proposed.
DNA Barcoding, Taxonomic Base Sequence Species Specificity Neural Networks, Computer Algorithms Reproducibility of Results Decision Trees Animals DNA Supervised Machine Learning Computational Biology Support Vector Machine Databases, Genetic Cluster Analysis
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Semi-supervised Learning Predicts Approximately One Third of the Alternative Splicing Isoforms as Functional Proteins.

Cell reports Jul 2, 2015
Alternative splicing acts on transcripts from almost all human multi-exon genes. Notwithstanding its ubiquity, fundamental ramifications of splicing on protein expression remain unresolved. The number and identity of spliced transcripts that form sta...
Humans Protein Isoforms Protein Structure, Tertiary ROC Curve Exons Proteins Alternative Splicing Area Under Curve Supervised Machine Learning
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The role of fine-grained annotations in supervised recognition of risk factors for heart disease from EHRs.

Journal of biomedical informatics Jun 26, 2015
This paper describes a supervised machine learning approach for identifying heart disease risk factors in clinical text, and assessing the impact of annotation granularity and quality on the system's ability to recognize these risk factors. We utiliz...
Vocabulary, Controlled Humans Data Mining Diabetes Complications Pattern Recognition, Automated Maryland Incidence Computer Security Cohort Studies Longitudinal Studies Male Natural Language Processing Electronic Health Records Narration Middle Aged Coronary Artery Disease Risk Assessment Female Confidentiality Comorbidity Aged Supervised Machine Learning
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Discriminative clustering via extreme learning machine.

Neural networks : the official journal of the International Neural Network Society Jun 19, 2015
Discriminative clustering is an unsupervised learning framework which introduces the discriminative learning rule of supervised classification into clustering. The underlying assumption is that a good partition (clustering) of the data should yield h...
Neural Networks, Computer Algorithms Cluster Analysis Discriminant Analysis Supervised Machine Learning Linear Models
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Automated tracing of myelinated axons and detection of the nodes of Ranvier in serial images of peripheral nerves.

Journal of microscopy Jun 12, 2015
The development of realistic neuroanatomical models of peripheral nerves for simulation purposes requires the reconstruction of the morphology of the myelinated fibres in the nerve, including their nodes of Ranvier. Currently, this information has to...
Ranvier's Nodes Datasets as Topic Microscopy, Electron Peripheral Nerves Vagus Nerve Algorithms Rats Supervised Machine Learning Animals Axons Imaging, Three-Dimensional
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EMD-Based Temporal and Spectral Features for the Classification of EEG Signals Using Supervised Learning.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Jun 8, 2015
This paper presents a novel method for feature extraction from electroencephalogram (EEG) signals using empirical mode decomposition (EMD). Its use is motivated by the fact that the EMD gives an effective time-frequency analysis of nonstationary sign...
Supervised Machine Learning Pattern Recognition, Automated Algorithms Reproducibility of Results Sensitivity and Specificity Spatio-Temporal Analysis Diagnosis, Computer-Assisted Electroencephalography Epilepsy Humans
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Recognition of activities of daily living in healthy subjects using two ad-hoc classifiers.

Biomedical engineering online Jun 6, 2015
BACKGROUND: Activities of daily living (ADL) are important for quality of life. They are indicators of cognitive health status and their assessment is a measure of independence in everyday living. ADL are difficult to reliably assess using questionna...
Algorithms Female Aged Adult Humans Circadian Rhythm Supervised Machine Learning Activities of Daily Living Healthy Volunteers Male Middle Aged Decision Trees Bayes Theorem Medical Records Sleep Neuropsychological Tests Infrared Rays Wireless Technology Accelerometry Thermometry
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Enhancement of ELM by Clustering Discrimination Manifold Regularization and Multiobjective FOA for Semisupervised Classification.

Computational intelligence and neuroscience May 27, 2015
A novel semisupervised extreme learning machine (ELM) with clustering discrimination manifold regularization (CDMR) framework named CDMR-ELM is proposed for semisupervised classification. By using unsupervised fuzzy clustering method, CDMR framework ...
Neural Networks, Computer Discriminant Analysis Algorithms Supervised Machine Learning Cluster Analysis
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Echocardiogram enhancement using supervised manifold denoising.

Medical image analysis May 21, 2015
This paper presents data-driven methods for echocardiogram enhancement. Existing denoising algorithms typically rely on a single noise model, and do not generalize to the composite noise sources typically found in real-world echocardiograms. Our meth...
Reproducibility of Results Image Enhancement Signal-To-Noise Ratio Sensitivity and Specificity Supervised Machine Learning Humans Echocardiography Image Interpretation, Computer-Assisted Algorithms Artifacts Pattern Recognition, Automated
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Accuracy of latent-variable estimation in Bayesian semi-supervised learning.

Neural networks : the official journal of the International Neural Network Society May 9, 2015
Hierarchical probabilistic models, such as Gaussian mixture models, are widely used for unsupervised learning tasks. These models consist of observable and latent variables, which represent the observable data and the underlying data-generation proce...
Models, Theoretical Normal Distribution Bayes Theorem Algorithms Cluster Analysis Supervised Machine Learning Models, Statistical Data Accuracy Regression Analysis Likelihood Functions
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