AIMC Topic: Data Interpretation, Statistical

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Causal models adjusting for time-varying confounding-a systematic review of the literature.

International journal of epidemiology Feb 1, 2019
BACKGROUND: Obtaining unbiased causal estimates from longitudinal observational data can be difficult due to exposure-affected time-varying confounding. The past decade has seen considerable development in methods for analysing such complex longitudi...
Computer Simulation Mental Health Health Status Humans Machine Learning Bias Probability Models, Statistical Confounding Factors, Epidemiologic Data Interpretation, Statistical Causality
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Statistical Learning Methods to Determine Immune Correlates of Herpes Zoster in Vaccine Efficacy Trials.

The Journal of infectious diseases Sep 22, 2018
Using Super Learner, a machine learning statistical method, we assessed varicella zoster virus-specific glycoprotein-based enzyme-linked immunosorbent assay (gpELISA) antibody titer as an individual-level signature of herpes zoster (HZ) risk in the Z...
Machine Learning Female Male Humans Randomized Controlled Trials as Topic Area Under Curve Herpes Zoster Herpes Zoster Vaccine Data Interpretation, Statistical ROC Curve Antibodies, Viral Middle Aged Models, Statistical Case-Control Studies
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PredPsych: A toolbox for predictive machine learning-based approach in experimental psychology research.

Behavior research methods Aug 1, 2018
Recent years have seen an increased interest in machine learning-based predictive methods for analyzing quantitative behavioral data in experimental psychology. While these methods can achieve relatively greater sensitivity compared to conventional u...
Machine Learning Data Interpretation, Statistical Behavioral Research Humans Psychology, Experimental
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Data-Adaptive Estimation for Double-Robust Methods in Population-Based Cancer Epidemiology: Risk Differences for Lung Cancer Mortality by Emergency Presentation.

American journal of epidemiology Apr 1, 2018
In this paper, we propose a structural framework for population-based cancer epidemiology and evaluate the performance of double-robust estimators for a binary exposure in cancer mortality. We conduct numerical analyses to study the bias and efficien...
Epidemiologic Research Design Emergency Service, Hospital Bayes Theorem Monte Carlo Method Likelihood Functions Socioeconomic Factors Machine Learning Sex Factors Female Models, Statistical Data Interpretation, Statistical Humans England Male Neoplasms Lung Neoplasms Risk Factors
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Application of Ontology Technology in Health Statistic Data Analysis.

Studies in health technology and informatics Jan 1, 2017
UNLABELLED: Research Purpose: establish health management ontology for analysis of health statistic data. Proposed Methods: this paper established health management ontology based on the analysis of the concepts in China Health Statistics Yearbook, a...
Humans Semantics Biological Ontologies Information Technology China Data Interpretation, Statistical
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Finding causative genes from high-dimensional data: an appraisal of statistical and machine learning approaches.

Statistical applications in genetics and molecular biology Aug 1, 2016
Modern biological experiments often involve high-dimensional data with thousands or more variables. A challenging problem is to identify the key variables that are related to a specific disease. Confounding this task is the vast number of statistical...
Neoplasms Models, Genetic Data Interpretation, Statistical Sample Size Machine Learning Computer Simulation Male Humans
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Statistical Inference for Data Adaptive Target Parameters.

The international journal of biostatistics May 1, 2016
Consider one observes n i.i.d. copies of a random variable with a probability distribution that is known to be an element of a particular statistical model. In order to define our statistical target we partition the sample in V equal size sub-samples...
Models, Statistical Data Interpretation, Statistical Biostatistics Machine Learning Data Mining
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Testing the Relative Performance of Data Adaptive Prediction Algorithms: A Generalized Test of Conditional Risk Differences.

The international journal of biostatistics May 1, 2016
Comparing the relative fit of competing models can be used to address many different scientific questions. In classical statistics one can, if appropriate, use likelihood ratio tests and information based criterion, whereas clinical medicine has tend...
Polymorphism, Single Nucleotide Genetic Association Studies Models, Statistical Machine Learning Risk Assessment Humans Data Interpretation, Statistical
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Variable Selection for Confounder Control, Flexible Modeling and Collaborative Targeted Minimum Loss-Based Estimation in Causal Inference.

The international journal of biostatistics May 1, 2016
This paper investigates the appropriateness of the integration of flexible propensity score modeling (nonparametric or machine learning approaches) in semiparametric models for the estimation of a causal quantity, such as the mean outcome under treat...
Machine Learning Models, Theoretical Outcome Assessment, Health Care Data Interpretation, Statistical Humans
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SAnDReS a Computational Tool for Statistical Analysis of Docking Results and Development of Scoring Functions.

Combinatorial chemistry & high throughput screening Jan 1, 2016
BACKGROUND: Docking allows to predict ligand binding to proteins, since the 3D-structure for the target is available. Several docking studies have been carried out to identify potential ligands for drug targets. Many of these studies resulted in the ...
Machine Learning Molecular Docking Simulation Data Interpretation, Statistical Databases, Protein
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