Evidence map›Paper›PMID 29460090›Full record

ArticleJournal of medical systems2018

Medical Big Data Warehouse: Architecture and System Design, a Case Study: Improving Healthcare Resources Distribution.

Abderrazak Sebaa, Fatima Chikh, Amina Nouicer, AbdelKamel Tari

Abstract read
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In one paragraph

Article in Journal of medical systems, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  13. Big data in IBD: a look into the future.Nature reviews. Gastroenterology & hepatology · 2019
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Abderrazak SebaaLIMED Laboratory, Faculty of Exact Sciences, University of Bejaia, Bejaia, Algeria. balzak.sebaa@gmail.com.ORCID http://orcid.org/0000-0002-8742-1240
Fatima ChikhDepartment of Computer Science, Faculty of Exact Sciences, University of Bejaia, Bejaia, Algeria.
Amina NouicerLIMED Laboratory, Faculty of Exact Sciences, University of Bejaia, Bejaia, Algeria.
AbdelKamel TariLIMED Laboratory, Faculty of Exact Sciences, University of Bejaia, Bejaia, Algeria.

Funding

Higher Education and Scientific Research of Algeria and the University of Bejaia B*00620140066/2015-2018
6 · The paper itself

Abstract

The huge increases in medical devices and clinical applications which generate enormous data have raised a big issue in managing, processing, and mining this massive amount of data. Indeed, traditional data warehousing frameworks can not be effective when managing the volume, variety, and velocity of current medical applications. As a result, several data warehouses face many issues over medical data and many challenges need to be addressed. New solutions have emerged and Hadoop is one of the best examples, it can be used to process these streams of medical data. However, without an efficient system design and architecture, these performances will not be significant and valuable for medical managers. In this paper, we provide a short review of the literature about research issues of traditional data warehouses and we present some important Hadoop-based data warehouses. In addition, a Hadoop-based architecture and a conceptual data model for designing medical Big Data warehouse are given. In our case study, we provide implementation detail of big data warehouse based on the proposed architecture and data model in the Apache Hadoop platform to ensure an optimal allocation of health resources.

Indexed as

Decision Support TechniquesAlgeriaHealth ResourcesHumansInformation Storage and RetrievalModels, TheoreticalBig dataData warehouseDecision supportHadoopMedical resources allocation

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.