AIMC Topic:
Bayes Theorem

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Intelligent diagnosis of jaundice with dynamic uncertain causality graph model.

Journal of Zhejiang University. Science. B May 1, 2017
Jaundice is a common and complex clinical symptom potentially occurring in hepatology, general surgery, pediatrics, infectious diseases, gynecology, and obstetrics, and it is fairly difficult to distinguish the cause of jaundice in clinical practice,...
Sensitivity and Specificity Prevalence Diagnosis, Computer-Assisted Algorithms Computer Simulation Reproducibility of Results Bayes Theorem Jaundice Computer Graphics Decision Support Systems, Clinical Causality Models, Statistical Humans Machine Learning
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Feature selection using a one dimensional naïve Bayes' classifier increases the accuracy of support vector machine classification of CDR3 repertoires.

Bioinformatics (Oxford, England) Apr 1, 2017
MOTIVATION: Somatic DNA recombination, the hallmark of vertebrate adaptive immunity, has the potential to generate a vast diversity of antigen receptor sequences. How this diversity captures antigen specificity remains incompletely understood. In thi...
Complementarity Determining Regions Receptors, Antigen, T-Cell, alpha-beta Bayes Theorem Amino Acids CD4-Positive T-Lymphocytes Humans Animals Support Vector Machine Databases, Genetic Mice, Inbred C57BL
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CellSort: a support vector machine tool for optimizing fluorescence-activated cell sorting and reducing experimental effort.

Bioinformatics (Oxford, England) Mar 15, 2017
MOTIVATION: High throughput screening by fluorescence activated cell sorting (FACS) is a common task in protein engineering and directed evolution. It can also be a rate-limiting step if high false positive or negative rates necessitate multiple roun...
Algorithms Support Vector Machine Bayes Theorem Flow Cytometry Yeasts Software Cell Separation
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Application of supervised machine learning algorithms for the classification of regulatory RNA riboswitches.

Briefings in functional genomics Mar 1, 2017
Riboswitches, the small structured RNA elements, were discovered about a decade ago. It has been the subject of intense interest to identify riboswitches, understand their mechanisms of action and use them in genetic engineering. The accumulation of ...
Riboswitch Bayes Theorem Humans Supervised Machine Learning Algorithms Markov Chains Models, Theoretical
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Screening Electronic Health Record-Related Patient Safety Reports Using Machine Learning.

Journal of patient safety Mar 1, 2017
INTRODUCTION: The objective of this study was to develop a semiautomated approach to screening cases that describe hazards associated with the electronic health record (EHR) from a mandatory, population-based patient safety reporting system.
Mandatory Reporting Medical Informatics Automation Pennsylvania Electronic Health Records Humans Bayes Theorem Machine Learning Data Mining Algorithms Patient Safety Databases, Factual
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Reliable bearing fault diagnosis using Bayesian inference-based multi-class support vector machines.

The Journal of the Acoustical Society of America Feb 1, 2017
This letter presents a multi-fault diagnosis scheme for bearings using hybrid features extracted from their acoustic emissions and a Bayesian inference-based one-against-all support vector machine (Bayesian OAASVM) for multi-class classification. The...
Materials Testing Equipment Failure Analysis Acoustics Motion Sound Support Vector Machine Equipment Failure Time Factors Bayes Theorem Models, Theoretical
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Development of Asian Non-Small Cell Lung Cancer Survival Prediction Model Using an Innovative Method of Bayesian Network.

Studies in health technology and informatics Jan 1, 2017
We constructed a novel prognostic model using an innovative method of Bayesian Network (BN) to predict Non-Small Cell Lung Cancer survival status within 5 years after operation in the Asian population. The proposed BN model could present the relation...
Asian People Lung Neoplasms Humans Carcinoma, Non-Small-Cell Lung Algorithms Bayes Theorem Prognosis
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Effects of Implementing a Tree Model of Diagnosis into a Bayesian Diagnostic Inference System.

Studies in health technology and informatics Jan 1, 2017
To estimate a diagnostic probability similarly to experts using answers to interviews, we developed a system that fundamentally behaves as a Bayesian model. For predefined interviews, we defined the sensitivity and specificity related to one or more ...
Humans Sensitivity and Specificity Decision Support Techniques Bayes Theorem Probability
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Using Machine Learning Models to Predict In-Hospital Mortality for ST-Elevation Myocardial Infarction Patients.

Studies in health technology and informatics Jan 1, 2017
Acute myocardial infarction is a major cause of hospitalization and mortality in China, where ST-elevation myocardial infarction (STEMI) is more severe and has a higher mortality rate. Accurate and interpretable prediction of in-hospital mortality is...
China Hospital Mortality Humans Bayes Theorem Myocardial Infarction Machine Learning Forecasting
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Comparison of machine-learning algorithms to build a predictive model for detecting undiagnosed diabetes - ELSA-Brasil: accuracy study.

Sao Paulo medical journal = Revista paulista de medicina Jan 1, 2017
CONTEXT AND OBJECTIVE:: Type 2 diabetes is a chronic disease associated with a wide range of serious health complications that have a major impact on overall health. The aims here were to develop and validate predictive models for detecting undiagnos...
Humans Female Reproducibility of Results Aged Neural Networks, Computer Algorithms Computer Simulation Logistic Models Bayes Theorem Feasibility Studies Supervised Machine Learning Middle Aged Brazil Diabetes Mellitus, Type 2 Adult Sensitivity and Specificity Male
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