The role of machine learning in clinical research: transforming the future of evidence generation
Background Interest in the application of machine learning (ML) to the design, conduct, and
analysis of clinical trials has grown, but the evidence base for such applications has not …
analysis of clinical trials has grown, but the evidence base for such applications has not …
Supervised machine learning: a brief primer
Abstract Machine learning is increasingly used in mental health research and has the
potential to advance our understanding of how to characterize, predict, and treat mental …
potential to advance our understanding of how to characterize, predict, and treat mental …
Causal inference and counterfactual prediction in machine learning for actionable healthcare
Big data, high-performance computing, and (deep) machine learning are increasingly
becoming key to precision medicine—from identifying disease risks and taking preventive …
becoming key to precision medicine—from identifying disease risks and taking preventive …
Principles of confounder selection
TJ VanderWeele - European journal of epidemiology, 2019 - Springer
Selecting an appropriate set of confounders for which to control is critical for reliable causal
inference. Recent theoretical and methodological developments have helped clarify a …
inference. Recent theoretical and methodological developments have helped clarify a …
What is machine learning? A primer for the epidemiologist
Q Bi, KE Goodman, J Kaminsky… - American journal of …, 2019 - academic.oup.com
Abstract Machine learning is a branch of computer science that has the potential to transform
epidemiologic sciences. Amid a growing focus on “Big Data,” it offers epidemiologists new …
epidemiologic sciences. Amid a growing focus on “Big Data,” it offers epidemiologists new …
Structural equation modeling in organizational research: The state of our science and some proposals for its future
The use of structural equation modeling (SEM) has grown substantially over the past 40
years within organizational research and beyond. There have been many different …
years within organizational research and beyond. There have been many different …
In-hospital mortality from severe COVID-19 in a tertiary care center in Mexico City; causes of death, risk factors and the impact of hospital saturation
A Olivas-Martinez, JL Cárdenas-Fragoso, JV Jiménez… - PloS one, 2021 - journals.plos.org
Background As the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)
pandemic has remained in Latin America, Mexico has become the third country with the …
pandemic has remained in Latin America, Mexico has become the third country with the …
[图书][B] Targeted learning in data science
MJ Van der Laan, S Rose - 2018 - Springer
This book builds on and is a sequel to our book Targeted Learning: Causal Inference for
Observational and Experimental Studies (2011). Since the publication of this first book on …
Observational and Experimental Studies (2011). Since the publication of this first book on …
Outcome-wide longitudinal designs for causal inference: a new template for empirical studies
TJ VanderWeele, MB Mathur, Y Chen - 2020 - projecteuclid.org
Outcome-Wide Longitudinal Designs for Causal Inference: A New Template for Empirical
Studies Page 1 Statistical Science 2020, Vol. 35, No. 3, 437–466 https://doi.org/10.1214/19-STS728 …
Studies Page 1 Statistical Science 2020, Vol. 35, No. 3, 437–466 https://doi.org/10.1214/19-STS728 …
An expanded obstetric comorbidity scoring system for predicting severe maternal morbidity
OBJECTIVE: To develop and validate an expanded obstetric comorbidity score for predicting
severe maternal morbidity that can be applied consistently across contemporary US patient …
severe maternal morbidity that can be applied consistently across contemporary US patient …