ArticleCurrent epidemiology reports2019
Data Science in Environmental Health Research.
Article in Current epidemiology reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Exposome-Wide Association Study of Body Mass Index Using a Novel Meta-Analytical Approach for Random Forest Models.Environmental health perspectives · 2024Pooled it
- Using data science to identify climate change and health adverse impacts and solutions in Africa: a scoping review.npj health systems · 2026Article
- A review of geospatial exposure models and approaches for health data integration.Journal of exposure science & environmental epidemiology · 2025Review
- FHIR PIT: a geospatial and spatiotemporal data integration pipeline to support subject-level clinical research.BMC medical informatics and decision making · 2025Article
- TAME 2.0: expanding and improving online data science training for environmental health research.Frontiers in toxicology · 2025Article
- Development of a multimodal geomarker pipeline to assess the impact of social, economic, and environmental factors on pediatric health outcomes.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Article
- Article
- Interdisciplinary data science to advance environmental health research and improve birth outcomes.Environmental research · 2021Article
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
purpose of reviewData science is an exploding trans-disciplinary field that aims to harness the power of data to gain information or insights on researcher-defined topics of interest. In this paper we review how data science can help advance environmental health research. RECENT
findingsWe discuss the concepts computationally scalable handling of Big Data and the design of efficient research data platforms, and how data science can provide solutions for methodological challenges in environmental health research, such as high-dimensional outcomes and exposures, and prediction models. Finally, we discuss tools for reproducible research. SUMMARY: In this paper we present opportunities to improve environmental research capabilities by embracing data science, and the pitfalls that environmental health researchers should avoid when employing data scientific approaches. Throughout the paper, we emphasize the need for environmental health researchers to collaborate more closely with biostatisticians and data scientists to ensure robust and interpretable results.
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.