ArticleJournal of the American Medical Informatics Association : JAMIA2019
People-powered data collaboratives: fueling data science with the health-related experiences of individuals.
Article in Journal of the American Medical Informatics Association : JAMIA, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed.
- Gut microbiome, big data and machine learning to promote precision medicine for cancer.Nature reviews. Gastroenterology & hepatology · 2020Review
- Review of Clinical Research Informatics.Yearbook of medical informatics · 2020Review
- Big Data in Context: Addressing the Twin Perils of Data Absenteeism and Chauvinism in the Context of Health Disparities Research.Journal of medical Internet research · 2020Article
- The Promise of Big Data and Digital Solutions in Building a Cardiovascular Learning System: Opportunities and Barriers.Methodist DeBakey cardiovascular journalReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
The creation of people-driven data collaboratives, with governance structures that enable participants to have a meaningful voice in issues surrounding the use of their own data, is a novel strategy to harness our growing capacity to develop and maintain immense data assets from the real health experiences of individuals.
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.