AIMC Topic: Classification

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Extreme learning machine for a new hybrid morphological/linear perceptron.

Neural networks : the official journal of the International Neural Network Society Dec 19, 2019
Morphological neural networks (MNNs) can be characterized as a class of artificial neural networks that perform an operation of mathematical morphology at every node, possibly followed by the application of an activation function. Morphological perce...
Neural Networks, Computer Classification Machine Learning
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A Tunable-Q wavelet transform and quadruple symmetric pattern based EEG signal classification method.

Medical hypotheses Dec 10, 2019
Electroencephalography (EEG) signals have been widely used to diagnose brain diseases for instance epilepsy, Parkinson's Disease (PD), Multiple Skleroz (MS), and many machine learning methods have been proposed to develop automated disease diagnosis ...
Electroencephalography Epilepsy Machine Learning Algorithms Classification Wavelet Analysis Brain Waves Signal Processing, Computer-Assisted Humans Datasets as Topic
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Deep supervised learning with mixture of neural networks.

Artificial intelligence in medicine Nov 18, 2019
Deep Neural Network (DNN), as a deep architectures, has shown excellent performance in classification tasks. However, when the data has different distributions or contains some latent non-observed factors, it is difficult for DNN to train a single mo...
Humans Neural Networks, Computer Computer Simulation Female Breast Neoplasms Algorithms Databases, Factual Handwriting Pattern Recognition, Automated Classification Diabetes Mellitus Supervised Machine Learning
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Joint Ranking SVM and Binary Relevance with robust Low-rank learning for multi-label classification.

Neural networks : the official journal of the International Neural Network Society Oct 18, 2019
Multi-label classification studies the task where each example belongs to multiple labels simultaneously. As a representative method, Ranking Support Vector Machine (Rank-SVM) aims to minimize the Ranking Loss and can also mitigate the negative influ...
Support Vector Machine Classification
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Why Cohen's Kappa should be avoided as performance measure in classification.

PloS one Sep 26, 2019
We show that Cohen's Kappa and Matthews Correlation Coefficient (MCC), both extended and contrasted measures of performance in multi-class classification, are correlated in most situations, albeit can differ in others. Indeed, although in the symmetr...
Datasets as Topic Classification Models, Theoretical Data Analysis Reproducibility of Results Supervised Machine Learning
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Automatic classification of free-text medical causes from death certificates for reactive mortality surveillance in France.

International journal of medical informatics Jul 6, 2019
BACKGROUND: Mortality surveillance is of fundamental importance to public health surveillance. The real-time recording of death certificates, thanks to Electronic Death Registration System (EDRS), provides valuable data for reactive mortality surveil...
France Classification Epidemiological Monitoring Death Certificates Disease Cause of Death Supervised Machine Learning Support Vector Machine Public Health Surveillance Adult Male Humans
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Cancer taxonomy: pathology beyond pathology.

European journal of cancer (Oxford, England : 1990) May 17, 2019
The way we categorise and classify cancer types dictates not only the way we diagnose and treat patients but also many of our decisions on biomarker and drug development. In addition, cancer taxonomy proves the ground truth for future discoveries in ...
Artificial Intelligence Reproducibility of Results Diagnosis, Computer-Assisted Predictive Value of Tests Neoplasms Humans Microscopy Biopsy Observer Variation Image Interpretation, Computer-Assisted Pathologists Classification
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An Open Science Approach to Artificial Intelligence in Healthcare.

Yearbook of medical informatics Apr 25, 2019
OBJECTIVES: Artificial Intelligence (AI) offers significant potential for improving healthcare. This paper discusses how an "open science" approach to AI tool development, data sharing, education, and research can support the clinical adoption of AI ...
Classification Information Dissemination Datasets as Topic Machine Learning Artificial Intelligence Delivery of Health Care Decision Support Systems, Clinical
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Discriminative multi-source adaptation multi-feature co-regression for visual classification.

Neural networks : the official journal of the International Neural Network Society Mar 12, 2019
Learning an effective visual classifier from few labeled samples is a challenging problem, which has motivated the multi-source adaptation scheme in machine learning. While the advantages of multi-source adaptation have been widely recognized, there ...
Feedback Pattern Recognition, Automated Machine Learning Classification
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Robust capped L1-norm twin support vector machine.

Neural networks : the official journal of the International Neural Network Society Feb 18, 2019
Twin support vector machine (TWSVM) is a classical and effective classifier for binary classification. However, its robustness cannot be guaranteed due to the utilization of squared L2-norm distance that can usually exaggerate the influence of outlie...
Classification Algorithms Support Vector Machine
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