AIMC Topic: Bayes Theorem

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Automated classification of neurological disorders of gait using spatio-temporal gait parameters.

Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology Feb 7, 2015
OBJECTIVE: Automated pattern recognition systems have been used for accurate identification of neurological conditions as well as the evaluation of the treatment outcomes. This study aims to determine the accuracy of diagnoses of (oto-)neurological g...
Gait Pattern Recognition, Automated Nervous System Diseases Support Vector Machine Muscle, Skeletal Humans Principal Component Analysis Bayes Theorem Artificial Intelligence Neural Networks, Computer Algorithms Aged Female Reproducibility of Results Aged, 80 and over Male Middle Aged Time Factors
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Bayes optimal template matching for spike sorting - combining fisher discriminant analysis with optimal filtering.

Journal of computational neuroscience Feb 5, 2015
Spike sorting, i.e., the separation of the firing activity of different neurons from extracellular measurements, is a crucial but often error-prone step in the analysis of neuronal responses. Usually, three different problems have to be solved: the d...
Algorithms Reproducibility of Results Models, Neurological Action Potentials Bayes Theorem Discriminant Analysis Benchmarking Neurons Normal Distribution Neural Networks, Computer
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A framework for final drive simultaneous failure diagnosis based on fuzzy entropy and sparse bayesian extreme learning machine.

Computational intelligence and neuroscience Feb 5, 2015
This research proposes a novel framework of final drive simultaneous failure diagnosis containing feature extraction, training paired diagnostic models, generating decision threshold, and recognizing simultaneous failure modes. In feature extraction ...
Fuzzy Logic Humans Bayes Theorem Neural Networks, Computer Pattern Recognition, Automated Artificial Intelligence Entropy Support Vector Machine
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Expert system for predicting reaction conditions: the Michael reaction case.

Journal of chemical information and modeling Feb 3, 2015
A generic chemical transformation may often be achieved under various synthetic conditions. However, for any specific reagents, only one or a few among the reported synthetic protocols may be successful. For example, Michael β-addition reactions may ...
Expert Systems Support Vector Machine Quantitative Structure-Activity Relationship Predictive Value of Tests Informatics Machine Learning Chemistry, Organic Bayes Theorem Indicators and Reagents Algorithms Catalysis Databases, Factual Models, Chemical Reproducibility of Results
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A fast gene selection method for multi-cancer classification using multiple support vector data description.

Journal of biomedical informatics Dec 27, 2014
For cancer classification problems based on gene expression, the data usually has only a few dozen sizes but has thousands to tens of thousands of genes which could contain a large number of irrelevant genes. A robust feature selection algorithm is r...
Colonic Neoplasms Pattern Recognition, Automated Oligonucleotide Array Sequence Analysis Gene Expression Regulation, Leukemic Leukemia Support Vector Machine Models, Statistical Bayes Theorem Gene Expression Neoplasms Gene Expression Profiling Diagnosis, Computer-Assisted Gene Expression Regulation, Neoplastic Humans Artificial Intelligence Software Algorithms
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Bayesian models trained with HTS data for predicting β-haematin inhibition and in vitro antimalarial activity.

Bioorganic & medicinal chemistry Dec 20, 2014
A large quantity of high throughput screening (HTS) data for antimalarial activity has become available in recent years. This includes both phenotypic and target-based activity. Realising the maximum value of these data remains a challenge. In this r...
Drug Discovery Plasmodium falciparum Bayes Theorem Models, Biological Antimalarials Humans Machine Learning Hemeproteins Malaria, Falciparum Parasitic Sensitivity Tests Small Molecule Libraries Databases, Pharmaceutical
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Improving the Mann-Whitney statistical test for feature selection: an approach in breast cancer diagnosis on mammography.

Artificial intelligence in medicine Dec 12, 2014
OBJECTIVE: This work addresses the theoretical description and experimental evaluation of a new feature selection method (named uFilter). The uFilter improves the Mann-Whitney U-test for reducing dimensionality and ranking features in binary classifi...
Radiographic Image Interpretation, Computer-Assisted Humans Chi-Square Distribution Mammography Machine Learning Linear Models Female Predictive Value of Tests Algorithms Reproducibility of Results Bayes Theorem Databases, Factual Breast Neoplasms Discriminant Analysis Diagnosis, Computer-Assisted Models, Statistical
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Stable feature selection for clinical prediction: exploiting ICD tree structure using Tree-Lasso.

Journal of biomedical informatics Dec 9, 2014
Modern healthcare is getting reshaped by growing Electronic Medical Records (EMR). Recently, these records have been shown of great value towards building clinical prediction models. In EMR data, patients' diseases and hospital interventions are capt...
Decision Making Regression Analysis Decision Trees Bayes Theorem Probability Reproducibility of Results Risk Factors Logistic Models Support Vector Machine Medical Informatics International Classification of Diseases Humans Algorithms Prognosis Electronic Health Records
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The Impact of Oversampling with SMOTE on the Performance of 3 Classifiers in Prediction of Type 2 Diabetes.

Medical decision making : an international journal of the Society for Medical Decision Making Dec 1, 2014
OBJECTIVE: To evaluate the impact of the synthetic minority oversampling technique (SMOTE) on the performance of probabilistic neural network (PNN), naïve Bayes (NB), and decision tree (DT) classifiers for predicting diabetes in a prospective cohort ...
Female Decision Trees Risk Factors Middle Aged Adult Bayes Theorem Sensitivity and Specificity Selection Bias Diabetes Mellitus, Type 2 Humans Male Iran Models, Theoretical Neural Networks, Computer Minority Groups Socioeconomic Factors Algorithms Prospective Studies
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Moving Away From Error-Related Potentials to Achieve Spelling Correction in P300 Spellers.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Nov 25, 2014
P300 spellers can provide a means of communication for individuals with severe neuromuscular limitations. However, its use as an effective communication tool is reliant on high P300 classification accuracies ( > 70%) to account for error revisions. E...
Reproducibility of Results Sensitivity and Specificity Natural Language Processing Bayes Theorem Pattern Recognition, Automated Brain-Computer Interfaces Event-Related Potentials, P300 Humans Communication Devices for People with Disabilities Word Processing Machine Learning Algorithms
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