AIMC Topic:
Bayes Theorem

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Perspectives on Speech Timing: Coupled Oscillator Modeling of Polish and Finnish.

Phonetica Feb 23, 2017
This stud y was ai med at analyzing empirical duration data for Polish spoken at different tempos using an updated version of the Coupled Oscillator Model of speech timing and rhythm variability (O'Dell and Nieminen, 1999, 2009). We use Bayesian infe...
Speech Acoustics Finland Phonetics Sampling Studies Bayes Theorem Humans Reaction Time Language Speech Perception Poland
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Feature Extraction and Classification of EHG between Pregnancy and Labour Group Using Hilbert-Huang Transform and Extreme Learning Machine.

Computational and mathematical methods in medicine Feb 19, 2017
Preterm birth (PTB) is the leading cause of perinatal mortality and long-term morbidity, which results in significant health and economic problems. The early detection of PTB has great significance for its prevention. The electrohysterogram (EHG) rel...
Humans Labor, Obstetric Uterine Contraction ROC Curve Monitoring, Physiologic Models, Statistical Medical Informatics Pregnancy Electronic Data Processing Female Bayes Theorem Machine Learning Reproducibility of Results Algorithms Signal Processing, Computer-Assisted Databases, Factual
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Identification of adverse drug-drug interactions through causal association rule discovery from spontaneous adverse event reports.

Artificial intelligence in medicine Feb 10, 2017
OBJECTIVE: Drug-drug interaction (DDI) is of serious concern, causing over 30% of all adverse drug reactions and resulting in significant morbidity and mortality. Early discovery of adverse DDI is critical to prevent patient harm. Spontaneous reporti...
Humans Machine Learning Data Mining Adverse Drug Reaction Reporting Systems Bayes Theorem Drug Interactions Drug-Related Side Effects and Adverse Reactions
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Bayesian Machine Learning Techniques for revealing complex interactions among genetic and clinical factors in association with extra-intestinal Manifestations in IBD patients.

AMIA ... Annual Symposium proceedings. AMIA Symposium Feb 10, 2017
The objective of the study is to assess the predictive performance of three different techniques as classifiers for extra-intestinal manifestations in 152 patients with Crohn's disease. Naïve Bayes, Bayesian Additive Regression Trees and Bayesian Net...
Genetic Predisposition to Disease Crohn Disease Female Humans Models, Statistical Data Mining Risk Factors Machine Learning Bayes Theorem Polymorphism, Genetic Male Algorithms
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Towards Comprehensive Clinical Abbreviation Disambiguation Using Machine-Labeled Training Data.

AMIA ... Annual Symposium proceedings. AMIA Symposium Feb 10, 2017
Abbreviation disambiguation in clinical texts is a problem handled well by fully supervised machine learning methods. Acquiring training data, however, is expensive and would be impractical for large numbers of abbreviations in specialized corpora. A...
Natural Language Processing Bayes Theorem Abbreviations as Topic Algorithms Electronic Health Records Logistic Models
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Understanding patient satisfaction with received healthcare services: A natural language processing approach.

AMIA ... Annual Symposium proceedings. AMIA Symposium Feb 10, 2017
Important information is encoded in free-text patient comments. We determine the most common topics in patient comments, design automatic topic classifiers, identify comments ' sentiment, and find new topics in negative comments. Our annotation schem...
Natural Language Processing Bayes Theorem Patient Satisfaction Terminology as Topic Outcome and Process Assessment, Health Care Humans Delivery of Health Care
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Application of Machine-Learning Models to Predict Tacrolimus Stable Dose in Renal Transplant Recipients.

Scientific reports Feb 8, 2017
Tacrolimus has a narrow therapeutic window and considerable variability in clinical use. Our goal was to compare the performance of multiple linear regression (MLR) and eight machine learning techniques in pharmacogenetic algorithm-based prediction o...
Humans Machine Learning Linear Models Drug Dosage Calculations Multivariate Analysis Cohort Studies Renal Insufficiency, Chronic Immunosuppressive Agents Bayes Theorem Tacrolimus Transplant Recipients Kidney Transplantation Precision Medicine Adult Female Male Middle Aged
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Predicting DPP-IV inhibitors with machine learning approaches.

Journal of computer-aided molecular design Feb 2, 2017
Dipeptidyl peptidase IV (DPP-IV) is a promising Type 2 diabetes mellitus (T2DM) drug target. DPP-IV inhibitors prolong the action of glucagon-like peptide-1 (GLP-1) and gastric inhibitory peptide (GIP), improve glucose homeostasis without weight gain...
Humans Machine Learning Molecular Docking Simulation Bayes Theorem Dipeptidyl Peptidase 4 Small Molecule Libraries Dipeptidyl-Peptidase IV Inhibitors Computer-Aided Design Drug Design Diabetes Mellitus, Type 2
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A Theoretical Analysis of Why Hybrid Ensembles Work.

Computational intelligence and neuroscience Jan 31, 2017
Inspired by the group decision making process, ensembles or combinations of classifiers have been found favorable in a wide variety of application domains. Some researchers propose to use the mixture of two different types of classification algorithm...
Pattern Recognition, Automated Artificial Intelligence Algorithms Bayes Theorem Humans
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A deep learning approach for the analysis of masses in mammograms with minimal user intervention.

Medical image analysis Jan 28, 2017
We present an integrated methodology for detecting, segmenting and classifying breast masses from mammograms with minimal user intervention. This is a long standing problem due to low signal-to-noise ratio in the visualisation of breast masses, combi...
Breast Mammography Bayes Theorem Radiographic Image Interpretation, Computer-Assisted Humans Machine Learning Female Sensitivity and Specificity Breast Neoplasms
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