ReviewBioMed research international2015
Toward a Literature-Driven Definition of Big Data in Healthcare.
Review in BioMed research international, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers, 4 of them syntheses 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
56 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- The Potential of Big Data Research in HealthCare for Medical Doctors' Learning.Journal of medical systems · 2021Pooled it
- Secondary use of standardized nursing care data for advancing nursing science and practice: a systematic review.Journal of the American Medical Informatics Association : JAMIA · 2019Pooled it
- Current status of use of big data and artificial intelligence in RMDs: a systematic literature review informing EULAR recommendations.RMD open · 2019Pooled it
- Evidence of Progress in Making Nursing Practice Visible Using Standardized Nursing Data: a Systematic Review.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2017Pooled it
- Medical artificial intelligence and the right to health.BMC medical ethics · 2026Article
- Multivariate Normal Distribution Method for a Virtual Cerebral Arterial Population.International journal for numerical methods in biomedical engineering · 2025Article
- Data science applied to the assessment of biological variation estimates.Advances in laboratory medicine · 2025Article
- Article
- SALUS-A Study on Self-Tonometry for Glaucoma Patients: Design and Implementation of the Electronic Case File.Applied clinical informatics · 2024Article
- Machine learning for healthcare that matters: Reorienting from technical novelty to equitable impact.PLOS digital health · 2024Article
- [Frequency and distribution of the active agent of intravitreal injections in German centers 2015-2021-An oregis study].Die Ophthalmologie · 2024Article
- The future of medicine: an outline attempt using state-of-the-art business and scientific trends.Frontiers in medicine · 2024Review
- Health Services Research: A Review for the Interventional Radiologist.Seminars in interventional radiology · 2023Review
- Worldwide Evolution of Vaccinable and Nonvaccinable Viral Skin Infections: Google Trends Analysis.JMIR dermatology · 2022Article
- Real World-Big Data Analytics in Healthcare.International journal of environmental research and public health · 2022Article
- Prediction of antischistosomal small molecules using machine learning in the era of big data.Molecular diversity · 2022Review
- Risks and Opportunities to Ensure Equity in the Application of Big Data Research in Public Health.Annual review of public health · 2022Review
- Artificial Intelligence-Based Framework for Analyzing Health Care Staff Security Practice: Mapping Review and Simulation Study.JMIR medical informatics · 2021Review
- Epidemiologic evolution of common cutaneous infestations and arthropod bites: A Google Trends analysis.JAAD international · 2021Article
- Dataset Growth in Medical Image Analysis Research.Journal of imaging · 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
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveThe aim of this study was to provide a definition of big data in healthcare.
methodsA systematic search of PubMed literature published until May 9, 2014, was conducted. We noted the number of statistical individuals (n) and the number of variables (p) for all papers describing a dataset. These papers were classified into fields of study. Characteristics attributed to big data by authors were also considered. Based on this analysis, a definition of big data was proposed.
resultsA total of 196 papers were included. Big data can be defined as datasets with Log(n∗p) ≥ 7. Properties of big data are its great variety and high velocity. Big data raises challenges on veracity, on all aspects of the workflow, on extracting meaningful information, and on sharing information. Big data requires new computational methods that optimize data management. Related concepts are data reuse, false knowledge discovery, and privacy issues.
conclusionBig data is defined by volume. Big data should not be confused with data reuse: data can be big without being reused for another purpose, for example, in omics. Inversely, data can be reused without being necessarily big, for example, secondary use of Electronic Medical Records (EMR) data.
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.