ArticleJournal of medical systems2015
Design and development of a medical big data processing system based on Hadoop.
Article in Journal of medical systems, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
What it found
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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
20 citing papers in PubMed.
- Peripheral Artery Disease (P.A.D.): Vascular Hemodynamic Simulation Using a Printed Circuit Board (PCB) Design.Bioengineering (Basel, Switzerland) · 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
- Biomedical Big Data Technologies, Applications, and Challenges for Precision Medicine: A Review.Global challenges (Hoboken, NJ) · 2024Review
- Predictive modeling the probability of suffering from metabolic syndrome using machine learning: A population-based study.Heliyon · 2022Article
- Understanding the Uptake of Big Data in Health Care: Protocol for a Multinational Mixed-Methods Study.JMIR research protocols · 2020Article
- What You Need to Know Before Implementing a Clinical Research Data Warehouse: Comparative Review of Integrated Data Repositories in Health Care Institutions.JMIR formative research · 2020Review
- How to Determine the Early Warning Threshold Value of Meteorological Factors on Influenza through Big Data Analysis and Machine Learning.Computational and mathematical methods in medicine · 2020Article
- A Novel Method for Detection and Progress Assessment of Visual Distortion Caused by Macular Disorder: A Central Serous Chorioretinopathy (CSR) Case Study.Vision (Basel, Switzerland) · 2019Article
- Big Data Analytics in Medicine and Healthcare.Journal of integrative bioinformatics · 2018Article
- Toward Hypertension Prediction Based on PPG-Derived HRV Signals: a Feasibility Study.Journal of medical systems · 2018Article
- Medical Big Data Warehouse: Architecture and System Design, a Case Study: Improving Healthcare Resources Distribution.Journal of medical systems · 2018Article
- An Efficient Middle Layer Platform for Medical Imaging Archives.Journal of healthcare engineering · 2018Article
- Point-of-Care-Testing in Acute Stroke Management: An Unmet Need Ripe for Technological Harvest.Biosensors · 2017Review
- Target of obstructive sleep apnea syndrome merge lung cancer: based on big data platform.Oncotarget · 2017Article
- Using Distributed Data over HBase in Big Data Analytics Platform for Clinical Services.Computational and mathematical methods in medicine · 2017Article
- Big Data in Health: a Literature Review from the Year 2005.Journal of medical systems · 2016Review
- Recognizing millions of consistently unidentified spectra across hundreds of shotgun proteomics datasets.Nature methods · 2016Article
- Effects of the performance management information system in improving performance: an empirical study in Shanghai Ninth People's Hospital.SpringerPlus · 2016Article
- Article
- Clinical data integration and processing challenges in healthcare caused by contemporary software design.Digital healthArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Secondary use of medical big data is increasingly popular in healthcare services and clinical research. Understanding the logic behind medical big data demonstrates tendencies in hospital information technology and shows great significance for hospital information systems that are designing and expanding services. Big data has four characteristics--Volume, Variety, Velocity and Value (the 4 Vs)--that make traditional systems incapable of processing these data using standalones. Apache Hadoop MapReduce is a promising software framework for developing applications that process vast amounts of data in parallel with large clusters of commodity hardware in a reliable, fault-tolerant manner. With the Hadoop framework and MapReduce application program interface (API), we can more easily develop our own MapReduce applications to run on a Hadoop framework that can scale up from a single node to thousands of machines. This paper investigates a practical case of a Hadoop-based medical big data processing system. We developed this system to intelligently process medical big data and uncover some features of hospital information system user behaviors. This paper studies user behaviors regarding various data produced by different hospital information systems for daily work. In this paper, we also built a five-node Hadoop cluster to execute distributed MapReduce algorithms. Our distributed algorithms show promise in facilitating efficient data processing with medical big data in healthcare services and clinical research compared with single nodes. Additionally, with medical big data analytics, we can design our hospital information systems to be much more intelligent and easier to use by making personalized recommendations.
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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.