Drug repurposing or repositioning is a technique whereby existing drugs are used to treat
emerging and challenging diseases, including COVID-19. Drug repurposing has become a …

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 …

Importance Patent foramen ovale (PFO)–associated strokes comprise approximately 10% of
ischemic strokes in adults aged 18 to 60 years. While device closure decreases stroke …

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 …

In the last few years, machine learning (ML) and artificial intelligence have seen a new wave
of publicity fueled by the huge and ever‐increasing amount of data and computational …

Propensity score matching (PSM) is a popular method in clinical researches to create a
balanced covariate distribution between treated and untreated groups. However, the …

Abstract Machines are increasingly doing “intelligent” things. Face recognition algorithms
use a large dataset of photos labeled as having a face or not to estimate a function that …

It is increasingly important to accurately and comprehensively estimate the effects of
particular clinical treatments. Although randomization is the current gold standard …

Estimating individual treatment effect (ITE) is a challenging problem in causal inference, due
to the missing counterfactuals and the selection bias. Existing ITE estimation methods …

Machine learning is a field at the intersection of statistics and computer science that uses
algorithms to extract information and knowledge from data. Its applications increasingly find …