Causal machine learning for predicting treatment outcomes
Causal machine learning (ML) offers flexible, data-driven methods for predicting treatment
outcomes including efficacy and toxicity, thereby supporting the assessment and safety of …
outcomes including efficacy and toxicity, thereby supporting the assessment and safety of …
A survey on causal inference
Causal inference is a critical research topic across many domains, such as statistics,
computer science, education, public policy, and economics, for decades. Nowadays …
computer science, education, public policy, and economics, for decades. Nowadays …
Redlines and greenspace: the relationship between historical redlining and 2010 greenspace across the United States
A Nardone, KE Rudolph… - Environmental health …, 2021 - ehp.niehs.nih.gov
Introduction: Redlining, a racist mortgage appraisal practice of the 1930s, established and
exacerbated racial residential segregation boundaries in the United States. Investment risk …
exacerbated racial residential segregation boundaries in the United States. Investment risk …
Precision medicine
MR Kosorok, EB Laber - Annual review of statistics and its …, 2019 - annualreviews.org
Precision medicine seeks to maximize the quality of health care by individualizing the health-
care process to the uniquely evolving health status of each patient. This endeavor spans a …
care process to the uniquely evolving health status of each patient. This endeavor spans a …
Using big data to emulate a target trial when a randomized trial is not available
Ideally, questions about comparative effectiveness or safety would be answered using an
appropriately designed and conducted randomized experiment. When we cannot conduct a …
appropriately designed and conducted randomized experiment. When we cannot conduct a …
Nationwide geospatial analysis of county racial and ethnic composition and public drinking water arsenic and uranium
There is no safe level of exposure to inorganic arsenic or uranium, yet recent studies
identified sociodemographic and regional inequalities in concentrations of these frequently …
identified sociodemographic and regional inequalities in concentrations of these frequently …
Selection bias due to loss to follow up in cohort studies
Selection bias due to loss to follow up represents a threat to the internal validity of estimates
derived from cohort studies. Over the past 15 years, stratification-based techniques as well …
derived from cohort studies. Over the past 15 years, stratification-based techniques as well …
Targeted maximum likelihood estimation for causal inference in observational studies
MS Schuler, S Rose - American journal of epidemiology, 2017 - academic.oup.com
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 …
epidemiologic literature. While many applications of causal effect estimation use propensity …
Effectiveness and safety of reduced dose non-vitamin K antagonist oral anticoagulants and warfarin in patients with atrial fibrillation: propensity weighted nationwide …
Objective To examine clinical effectiveness and safety of apixaban 2.5 mg, dabigatran 110
mg, and rivaroxaban 15 mg compared with warfarin among patients with atrial fibrillation …
mg, and rivaroxaban 15 mg compared with warfarin among patients with atrial fibrillation …
Renin–angiotensin system blockers and susceptibility to COVID-19: an international, open science, cohort analysis
Background Angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor
blockers (ARBs) have been postulated to affect susceptibility to COVID-19. Observational …
blockers (ARBs) have been postulated to affect susceptibility to COVID-19. Observational …