ArticleAmerican journal of epidemiology2022
The Future of Causal Inference.
Article in American journal of epidemiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
15 citing papers in PubMed.
- Dynamic Bayesian networks to predict loss of kidney function: a cross-institution use case in a large cohort with or at-risk of CKD.BMC medical informatics and decision making · 2026Article
- A pipeline for enabling path-specific causal fairness in observational health data.Proceedings of the ... Conference on Fairness, Accountability, and Transparency · 2026Article
- Data Fusion for Partial Identification of Causal Effects.Advances in neural information processing systems · 2025Article
- AAdvances in neural information processing systems · 2025Article
- Impact of Near-Positivity Violations on IPTW-Estimated Marginal Structural Survival Models With Time-Dependent Confounding.Biometrical journal. Biometrische Zeitschrift · 2025Article
- Artificial Intelligence for the Diagnosis and Management of Cancers: Potentials and Challenges.MedComm · 2025Review
- Chronic kidney disease and dementia: an epidemiological perspective.Nature reviews. Nephrology · 2025Review
- Causal mediation analysis: what is it and how can it be used to inform practice and policy?Family practice · 2025Article
- On the current and future potential of simulations based on directed acyclic graphs.Global epidemiology · 2025Article
- Considerations for Causal Inference Studies.Respirology (Carlton, Vic.) · 2025Article
- When, why and how are estimated effects transported between populations? A scoping review of studies applying transportability methods.European journal of epidemiology · 2025Article
- Pathways to chronic disease detection and prediction: Mapping the potential of machine learning to the pathophysiological processes while navigating ethical challenges.Chronic diseases and translational medicine · 2025Review
- Step-by-step causal analysis of EHRs to ground decision-making.PLOS digital health · 2025Article
- Single World Intervention Graphs (SWIGs): A Practical Guide.American journal of epidemiology · 2024Article
- Potential of artificial intelligence in injury prevention research and practice.Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.