ArticleInternational journal of epidemiology2021
Intersections of machine learning and epidemiological methods for health services research.
Article in International journal of epidemiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 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
21 citing papers in PubMed.
- A five-year risk prediction model of cardiovascular disease in individuals with bipolar disorder: a nationwide register study from Sweden.Molecular psychiatry · 2026Article
- Ten Healthcare Delivery Trends and Their Measurement and Methodological Implications for Cancer Health Services Research.Health services research · 2026Article
- Unbound bilirubin and risk of severe neurodevelopmental impairment in extremely low birthweight newborns.Pediatric research · 2025Article
- Regularized regression outperforms trees for predicting cognitive function in the Health and Retirement Study.Machine learning with applications · 2025Article
- Explainable machine learning for health disparities: type 2 diabetes in thebioRxiv : the preprint server for biology · 2025Article
- Leveraging Random Forests explainability for predictive modeling of children's conduct problems: insights from individual and family factors.Frontiers in public health · 2025Article
- Leveraging Machine Learning to Identify Subgroups of Misclassified Patients in the Emergency Department: Multicenter Proof-of-Concept Study.Journal of medical Internet research · 2024Article
- Social Determinants of Health and the Use of Community-Based Rehabilitation Following Stroke: Methodologic Considerations.Archives of rehabilitation research and clinical translation · 2024Article
- Twenty-four-hour physical activity patterns associated with depressive symptoms: a cross-sectional study using big data-machine learning approach.BMC public health · 2024Article
- A glimpse into the future: modelling global prevalence of hypertension.BMC public health · 2023Article
- Co-evolution of epidemiology and artificial intelligence: challenges and opportunities.International journal of epidemiology · 2023Article
- Article
- Mapping of machine learning approaches for description, prediction, and causal inference in the social and health sciences.Science advances · 2022Review
- Using random forest to identify longitudinal predictors of health in a 30-year cohort study.Scientific reports · 2022Article
- Reproducibility of prediction models in health services research.BMC research notes · 2022Article
- Current Artificial Intelligence (AI) Techniques, Challenges, and Approaches in Controlling and Fighting COVID-19: A Review.International journal of environmental research and public health · 2022Review
- Multivariable prediction models for health care spending using machine learning: a protocol of a systematic review.Diagnostic and prognostic research · 2022Article
- Is the Way Forward to Step Back? Documenting the Frequency With Which Study Goals Are Misaligned With Study Methods and Interpretations in the Epidemiologic Literature.Epidemiologic reviews · 2022Observational
- Machine Learning for Causal Inference in Biological Networks: Perspectives of This Challenge.Frontiers in bioinformatics · 2021Article
- [Perspectives for rheumatological health services research at the German Rheumatism Research Center].Zeitschrift fur Rheumatologie · 2020Review
Corrections and comments
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Authors and funding
1 author.
Funding
Abstract
The field of health services research is broad and seeks to answer questions about the health care system. It is inherently interdisciplinary, and epidemiologists have made crucial contributions. Parametric regression techniques remain standard practice in health services research with machine learning techniques currently having low penetrance in comparison. However, studies in several prominent areas, including health care spending, outcomes and quality, have begun deploying machine learning tools for these applications. Nevertheless, major advances in epidemiological methods are also as yet underleveraged in health services research. This article summarizes the current state of machine learning in key areas of health services research, and discusses important future directions at the intersection of machine learning and epidemiological methods for health services research.
Indexed as
Identifiers
What Socratic 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 Socratic graph.