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.
Original language | English (US) |
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Pages (from-to) | 1671-1676 |
Number of pages | 6 |
Journal | American journal of epidemiology |
Volume | 191 |
Issue number | 10 |
DOIs | |
State | Published - Oct 1 2022 |
Externally published | Yes |
All Science Journal Classification (ASJC) codes
- Medicine(all)
Keywords
- algorithms
- causal discovery
- causal machine learning
- distributed learning
- high-dimensional data
- interference
- transportability