The Future of Causal Inference. Issue 10 (28th June 2022)

• Record Type: Journal Article
• Authors: Mitra, Nandita; Roy, Jason; Small, Dylan
• Is Part Of: American journal of epidemiology. Volume 191:Issue 10(2022)
• Page Start: 1671
• Page End: 1676
• Publication Date: 2022-06-28
• Subjects: algorithms -- causal discovery -- causal machine learning -- distributed learning -- high-dimensional data -- interference -- transportability; Epidemiology -- Periodicals; Public health -- Periodicals; 614.4
• DOI: 10.1093/aje/kwac108
• Languages: English
• ISSNs: 0002-9262

Abstract

Abstract: The past several decades have seen exponential growth in causal inference approaches and their applications. In this commentary, we provide our top-10 list of emerging and exciting areas of research in causal inference. These include methods for high-dimensional data and precision medicine, causal machine learning, causal discovery, and others. These methods are not meant to be an exhaustive list; instead, we hope that this list will serve as a springboard for stimulating the development of new research.