ReviewBiomedical informatics insights2016
Big Data Application in Biomedical Research and Health Care: A Literature Review.
Review in Biomedical informatics insights, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 118 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
118 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A Systematic Review of Predictors of Vaping Cessation Among Young People.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2025Pooled it
- Exploring data reduction strategies in the analysis of continuous pressure imaging technology.BMC medical research methodology · 2023Trial
- Does an interactive trust-enhanced electronic consent improve patient experiences when asked to share their health records for research? A randomized trial.Journal of the American Medical Informatics Association : JAMIA · 2019Trial
- Review
- Attitudes toward artificial intelligence: their association with creative self-efficacy and problem-solving ability in nursing interns.BMC nursing · 2026Article
- Methodological Development and Assessing Prescribing Determinants Through Cumulative Drug Exposure in Hospitalized Patients: Proof-of-Concept Retrospective Study.JMIR medical informatics · 2026Article
- Population-level cardiovascular risk prediction models including biochemical predictors in 800 000 individuals.European heart journal open · 2026Article
- Lessons Learned From Building a Data Platform for Longitudinal, Analytical Use Cases and Scaling to 77 German Hospitals: Implementation Report.JMIR medical informatics · 2025Article
- Revolutionizing multi-omics analysis with artificial intelligence and data processing.Quantitative biology (Beijing, China) · 2025Review
- BioRAGent: natural language biomedical querying with retrieval-augmented multiagent systems.Briefings in bioinformatics · 2025Article
- BifurcatoR: A Framework for Revealing Clinically Actionable Signal in Variance Masquerading as Noise.bioRxiv : the preprint server for biology · 2025Article
- Reanalysis of Published Histological Data Can Help to Characterize Neuronal Death After Spinal Cord Injury.International journal of molecular sciences · 2025Article
- TICS-M scores in an oldest-old normative cohort identified by computable phenotype.The Clinical neuropsychologist · 2025Article
- Article
- Navigating ethics in HIV data and biomaterial management within Black, African, and Caribbean communities in Canada.BMC medical ethics · 2025Article
- Annotated corpus for traditional formula-disease relationships in biomedical articles.Scientific data · 2025Article
- The Super Spreadsheet: collaborative information infrastructure in translational teams.Frontiers in psychology · 2025Article
- Demographic factors, knowledge, attitude and perception and their association with nursing students' intention to use artificial intelligence (AI): a multicentre survey across 10 Arab countries.BMC medical education · 2024Article
- Unveiling microbial communities with EasyAmplicon: A user-centric guide to perform amplicon sequencing data analysis.iMetaOmics · 2024Article
- Implications of Big Data Analytics, AI, Machine Learning, and Deep Learning in the Health Care System of Bangladesh: Scoping Review.Journal of medical Internet research · 2024Article
58 more citing papers are in PubMed but not listed here.
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
Big data technologies are increasingly used for biomedical and health-care informatics research. Large amounts of biological and clinical data have been generated and collected at an unprecedented speed and scale. For example, the new generation of sequencing technologies enables the processing of billions of DNA sequence data per day, and the application of electronic health records (EHRs) is documenting large amounts of patient data. The cost of acquiring and analyzing biomedical data is expected to decrease dramatically with the help of technology upgrades, such as the emergence of new sequencing machines, the development of novel hardware and software for parallel computing, and the extensive expansion of EHRs. Big data applications present new opportunities to discover new knowledge and create novel methods to improve the quality of health care. The application of big data in health care is a fast-growing field, with many new discoveries and methodologies published in the last five years. In this paper, we review and discuss big data application in four major biomedical subdisciplines: (1) bioinformatics, (2) clinical informatics, (3) imaging informatics, and (4) public health informatics. Specifically, in bioinformatics, high-throughput experiments facilitate the research of new genome-wide association studies of diseases, and with clinical informatics, the clinical field benefits from the vast amount of collected patient data for making intelligent decisions. Imaging informatics is now more rapidly integrated with cloud platforms to share medical image data and workflows, and public health informatics leverages big data techniques for predicting and monitoring infectious disease outbreaks, such as Ebola. In this paper, we review the recent progress and breakthroughs of big data applications in these health-care domains and summarize the challenges, gaps, and opportunities to improve and advance big data applications in health care.
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.