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Classification

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Why Cohen's Kappa should be avoided as performance measure in classification.

PloS one 31557204
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...
Classification Data Analysis Datasets as Topic Models, Theoretical 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 31522022
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...
Adult Cause of Death Classification Death Certificates Disease Epidemiological Monitoring France Humans Male Public Health Surveillance Supervised Machine Learning Support Vector Machine
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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 31675625
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...
Classification Support Vector Machine
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Evaluating shallow and deep learning strategies for the 2018 n2c2 shared task on clinical text classification.

Journal of the American Medical Informatics Association : JAMIA 31512729
OBJECTIVE: Automated clinical phenotyping is challenging because word-based features quickly turn it into a high-dimensional problem, in which the small, privacy-restricted, training datasets might lead to overfitting. Pretrained embeddings might sol...
Classification Clinical Trials as Topic Data Mining Deep Learning Humans Logistic Models Machine Learning Natural Language Processing Neural Networks, Computer Patient Selection
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ML-Net: multi-label classification of biomedical texts with deep neural networks.

Journal of the American Medical Informatics Association : JAMIA 31233120
OBJECTIVE: In multi-label text classification, each textual document is assigned 1 or more labels. As an important task that has broad applications in biomedicine, a number of different computational methods have been proposed. Many of these methods,...
Benchmarking Classification Computational Biology Data Mining Deep Learning Machine Learning Natural Language Processing Neural Networks, Computer
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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 31891839
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...
Classification Machine Learning Neural Networks, Computer
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A Tunable-Q wavelet transform and quadruple symmetric pattern based EEG signal classification method.

Medical hypotheses 31877443
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 ...
Algorithms Brain Waves Classification Datasets as Topic Electroencephalography Epilepsy Humans Machine Learning Signal Processing, Computer-Assisted Wavelet Analysis
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Using convolutional neural networks to identify patient safety incident reports by type and severity.

Journal of the American Medical Informatics Association : JAMIA 31730700
OBJECTIVE: To evaluate the feasibility of a convolutional neural network (CNN) with word embedding to identify the type and severity of patient safety incident reports.
Classification Feasibility Studies Humans Medical Errors Neural Networks, Computer Patient Safety Risk Management Support Vector Machine
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Imputation and characterization of uncoded self-harm in major mental illness using machine learning.

Journal of the American Medical Informatics Association : JAMIA 31651956
OBJECTIVE: We aimed to impute uncoded self-harm in administrative claims data of individuals with major mental illness (MMI), characterize self-harm incidence, and identify factors associated with coding bias.
Adult Algorithms Classification Clinical Coding Datasets as Topic Electronic Health Records Female Humans Incidence Machine Learning Male Mental Disorders Self-Injurious Behavior Suicidal Ideation
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Accurate Inference of Tree Topologies from Multiple Sequence Alignments Using Deep Learning.

Systematic biology 31504938
Reconstructing the phylogenetic relationships between species is one of the most formidable tasks in evolutionary biology. Multiple methods exist to reconstruct phylogenetic trees, each with their own strengths and weaknesses. Both simulation and emp...
Classification Computer Simulation Deep Learning Neural Networks, Computer Phylogeny Sequence Alignment
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