AIMC Topic: Epidemiologic Research Design

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Machine Learning in Epidemiology and Health Outcomes Research.

Annual review of public health Oct 2, 2019
Machine learning approaches to modeling of epidemiologic data are becoming increasingly more prevalent in the literature. These methods have the potential to improve our understanding of health and opportunities for intervention, far beyond our past ...
Humans Machine Learning Outcome Assessment, Health Care Epidemiologic Methods Epidemiologic Research Design
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Targeted Maximum Likelihood Estimation for Causal Inference in Observational Studies.

American journal of epidemiology Dec 9, 2016
Estimation of causal effects using observational data continues to grow in popularity in the epidemiologic literature. While many applications of causal effect estimation use propensity score methods or G-computation, targeted maximum likelihood esti...
Humans Machine Learning Computer Simulation Exercise Depression Causality Observational Studies as Topic Data Interpretation, Statistical Bias Propensity Score Likelihood Functions Confounding Factors, Epidemiologic Epidemiologic Research Design
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Signals Among Signals: Prioritizing Nongenetic Associations in Massive Data Sets.

American journal of epidemiology May 1, 2019
Massive data sets are often regarded as a panacea to the underpowered studies of the past. At the same time, it is becoming clear that in many of these data sets in which thousands of variables are measured across hundreds of thousands or millions of...
Humans Machine Learning Big Data Models, Statistical Data Interpretation, Statistical Confounding Factors, Epidemiologic Biostatistics Epidemiologic Research Design
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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...
Humans Machine Learning Female Risk Factors Male Neoplasms England Lung Neoplasms Socioeconomic Factors Models, Statistical Data Interpretation, Statistical Emergency Service, Hospital Bayes Theorem Sex Factors Monte Carlo Method Likelihood Functions Epidemiologic Research Design
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