AIMC Topic: Logistic Models

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Estimating psychopathological networks: Be careful what you wish for.

PloS one Jun 23, 2017
Network models, in which psychopathological disorders are conceptualized as a complex interplay of psychological and biological components, have become increasingly popular in the recent psychopathological literature (Borsboom, et. al., 2011). These ...
Humans Neural Networks, Computer Research Design Multivariate Analysis Psychopathology Logistic Models Datasets as Topic
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Laboratory parameter-based machine learning model for excluding non-alcoholic fatty liver disease (NAFLD) in the general population.

Alimentary pharmacology & therapeutics Jun 6, 2017
BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) affects 20%-40% of the general population in developed countries and is an increasingly important cause of hepatocellular carcinoma. Electronic medical records facilitate large-scale epidemiologic...
Sensitivity and Specificity Cross-Sectional Studies Male Middle Aged Machine Learning Female Adult Anthropometry Alanine Transaminase Lipoproteins, HDL Triglycerides Humans ROC Curve Logistic Models Non-alcoholic Fatty Liver Disease
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Dysphonic Voice Pattern Analysis of Patients in Parkinson's Disease Using Minimum Interclass Probability Risk Feature Selection and Bagging Ensemble Learning Methods.

Computational and mathematical methods in medicine May 3, 2017
Analysis of quantified voice patterns is useful in the detection and assessment of dysphonia and related phonation disorders. In this paper, we first study the linear correlations between 22 voice parameters of fundamental frequency variability, ampl...
Parkinson Disease ROC Curve Voice Logistic Models Support Vector Machine Humans Machine Learning Algorithms
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Exploration of machine learning techniques in predicting multiple sclerosis disease course.

PloS one Apr 5, 2017
OBJECTIVE: To explore the value of machine learning methods for predicting multiple sclerosis disease course.
Multiple Sclerosis Neuroimaging Logistic Models Support Vector Machine Magnetic Resonance Imaging Sensitivity and Specificity Machine Learning Male Humans Disease Progression Brain Female Adult
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Can machine-learning improve cardiovascular risk prediction using routine clinical data?

PloS one Apr 4, 2017
BACKGROUND: Current approaches to predict cardiovascular risk fail to identify many people who would benefit from preventive treatment, while others receive unnecessary intervention. Machine-learning offers opportunity to improve accuracy by exploiti...
Humans Algorithms Prospective Studies Neural Networks, Computer Machine Learning Cardiovascular Diseases Aged Middle Aged Aged, 80 and over Logistic Models Cohort Studies Electronic Health Records Adult Female Male Risk Factors
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Using classification tree analysis to generate propensity score weights.

Journal of evaluation in clinical practice Mar 28, 2017
RATIONALE, AIMS AND OBJECTIVES: In evaluating non-randomized interventions, propensity scores (PS) estimate the probability of assignment to the treatment group given observed characteristics. Machine learning algorithms have been proposed as an alte...
Computer Simulation Logistic Models Observational Studies as Topic Propensity Score Monte Carlo Method Models, Statistical Data Interpretation, Statistical Humans Machine Learning
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Prediction of virus-host infectious association by supervised learning methods.

BMC bioinformatics Mar 14, 2017
BACKGROUND: The study of virus-host infectious association is important for understanding the functions and dynamics of microbial communities. Both cellular and fractionated viral metagenomic data generate a large number of viral contigs with missing...
Logistic Models Models, Theoretical Support Vector Machine Reproducibility of Results ROC Curve Bacteria Metagenomics Host-Pathogen Interactions Genome, Viral Likelihood Functions DNA, Viral Sequence Analysis, DNA Bayes Theorem Viruses
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MOST: most-similar ligand based approach to target prediction.

BMC bioinformatics Mar 11, 2017
BACKGROUND: Many computational approaches have been used for target prediction, including machine learning, reverse docking, bioactivity spectra analysis, and chemical similarity searching. Recent studies have suggested that chemical similarity searc...
Ligands Acetylcholinesterase Emodin Aloe Animals Databases, Chemical Humans Logistic Models Cathartics Machine Learning Kinetics
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Predictive model for 5-year mortality after breast cancer surgery in Taiwan residents.

Chinese journal of cancer Feb 27, 2017
BACKGROUND: Few studies of breast cancer surgery outcomes have used longitudinal data for more than 2 years. This study aimed to validate the use of the artificial neural network (ANN) model to predict the 5-year mortality of breast cancer patients a...
Proportional Hazards Models Breast Neoplasms Neural Networks, Computer Logistic Models Taiwan Female Humans
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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 Algorithms Bayes Theorem Electronic Health Records Abbreviations as Topic Logistic Models
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