AIMC Topic: Bayes Theorem

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Using machine learning to support healthcare professionals in making preauthorisation decisions.

International journal of medical informatics Jun 16, 2016
BACKGROUND: Preauthorisation is a control mechanism that is used by Health Insurance Providers (HIPs) to minimise wastage of resources through the denial of the procedures that were unduly requested. However, an efficient preauthorisation process req...
Support Vector Machine Bayes Theorem Algorithms Health Personnel Clinical Decision-Making Artificial Intelligence Machine Learning Humans
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Statistical Performance Analysis of Data-Driven Neural Models.

International journal of neural systems Jun 9, 2016
Data-driven model-based analysis of electrophysiological data is an emerging technique for understanding the mechanisms of seizures. Model-based analysis enables tracking of hidden brain states that are represented by the dynamics of neural mass mode...
Neural Networks, Computer Algorithms Brain Computer Simulation Humans Synapses Stochastic Processes Uncertainty Membrane Potentials Epilepsy Seizures Neurons Models, Neurological Data Interpretation, Statistical Bayes Theorem
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A Multilayer Perceptron Based Smart Pathological Brain Detection System by Fractional Fourier Entropy.

Journal of medical systems Jun 2, 2016
This work aims at developing a novel pathological brain detection system (PBDS) to assist neuroradiologists to interpret magnetic resonance (MR) brain images. We simplify this problem as recognizing pathological brains from healthy brains. First, 12 ...
Humans Magnetic Resonance Imaging Bayes Theorem Brain Diseases Fourier Analysis Neural Networks, Computer Algorithms Image Processing, Computer-Assisted
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Fitting the data from embryo implantation prediction: Learning from label proportions.

Statistical methods in medical research May 30, 2016
Machine learning techniques have been previously used to assist clinicians to select embryos for human-assisted reproduction. This work aims to show how an appropriate modeling of the problem can contribute to improve machine learning techniques for ...
Bayes Theorem Spain Reproductive Techniques, Assisted Machine Learning Databases, Factual Embryo Implantation Humans
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Intrinsic Plasticity for Natural Competition in Koniocortex-Like Neural Networks.

International journal of neural systems May 16, 2016
In this paper, we use the neural property known as intrinsic plasticity to develop neural network models that resemble the koniocortex, the fourth layer of sensory cortices. These models evolved from a very basic two-layered neural network to a compl...
Thalamus Neural Inhibition Computer Simulation Neuronal Plasticity Models, Neurological Cerebral Cortex Neural Pathways Bayes Theorem Neurons Machine Learning Software Algorithms Humans Neural Networks, Computer
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A study of the effectiveness of machine learning methods for classification of clinical interview fragments into a large number of categories.

Journal of biomedical informatics May 13, 2016
This study examines the effectiveness of state-of-the-art supervised machine learning methods in conjunction with different feature types for the task of automatic annotation of fragments of clinical text based on codebooks with a large number of cat...
Semantics Data Curation Decision Trees Bayes Theorem Machine Learning Support Vector Machine
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Machine Learning and Computer Vision System for Phenotype Data Acquisition and Analysis in Plants.

Sensors (Basel, Switzerland) May 5, 2016
Phenomics is a technology-driven approach with promising future to obtain unbiased data of biological systems. Image acquisition is relatively simple. However data handling and analysis are not as developed compared to the sampling capacities. We pre...
Algorithms Phenotype Support Vector Machine Artificial Intelligence Bayes Theorem Plants
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A hierarchical model for integrating unsupervised generative embedding and empirical Bayes.

Journal of neuroscience methods Apr 30, 2016
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...
Models, Neurological Models, Statistical Unsupervised Machine Learning Markov Chains Neuroimaging Bayes Theorem Schizophrenia Male Magnetic Resonance Imaging Cluster Analysis Female Reproducibility of Results Adult Monte Carlo Method Humans Software Brain Computer Simulation
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Incorporating organelle correlations into semi-supervised learning for protein subcellular localization prediction.

Bioinformatics (Oxford, England) Apr 23, 2016
MOTIVATION: Bioimages of subcellular protein distribution as a new data source have attracted much attention in the field of automated prediction of proteins subcellular localization. Performance of existing systems is significantly limited by the sm...
Bayes Theorem Supervised Machine Learning Immunohistochemistry Humans Algorithms Computational Biology Protein Transport Fluorescent Antibody Technique Organelles
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Sparse Bayesian Learning for Obtaining Sparsity of EEG Frequency Bands Based Feature Vectors in Motor Imagery Classification.

International journal of neural systems Apr 11, 2016
Effective common spatial pattern (CSP) feature extraction for motor imagery (MI) electroencephalogram (EEG) recordings usually depends on the filter band selection to a large extent. Subband optimization has been suggested to enhance classification a...
Discriminant Analysis Electroencephalography Datasets as Topic Motor Activity Imagination Linear Models Brain-Computer Interfaces Brain Time Factors Bayes Theorem Humans Machine Learning Algorithms
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