| Title |
A Systematic Review of Techniques and Sources of Big Data in the Healthcare Sector
|
|---|---|
| Published in |
Journal of Medical Systems, October 2017
|
| DOI | 10.1007/s10916-017-0832-2 |
| Pubmed ID | |
| Authors |
Susel Góngora Alonso, Isabel de la Torre Díez, Joel J. P. C. Rodrigues, Sofiane Hamrioui, Miguel López-Coronado |
| Abstract |
The main objective of this paper is to present a review of existing researches in the literature, referring to Big Data sources and techniques in health sector and to identify which of these techniques are the most used in the prediction of chronic diseases. Academic databases and systems such as IEEE Xplore, Scopus, PubMed and Science Direct were searched, considering the date of publication from 2006 until the present time. Several search criteria were established as 'techniques' OR 'sources' AND 'Big Data' AND 'medicine' OR 'health', 'techniques' AND 'Big Data' AND 'chronic diseases', etc. Selecting the paper considered of interest regarding the description of the techniques and sources of Big Data in healthcare. It found a total of 110 articles on techniques and sources of Big Data on health from which only 32 have been identified as relevant work. Many of the articles show the platforms of Big Data, sources, databases used and identify the techniques most used in the prediction of chronic diseases. From the review of the analyzed research articles, it can be noticed that the sources and techniques of Big Data used in the health sector represent a relevant factor in terms of effectiveness, since it allows the application of predictive analysis techniques in tasks such as: identification of patients at risk of reentry or prevention of hospital or chronic diseases infections, obtaining predictive models of quality. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 1 | 33% |
| United Kingdom | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 188 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 188 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 29 | 15% |
| Student > Ph. D. Student | 27 | 14% |
| Researcher | 25 | 13% |
| Student > Bachelor | 15 | 8% |
| Lecturer | 9 | 5% |
| Other | 37 | 20% |
| Unknown | 46 | 24% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 40 | 21% |
| Medicine and Dentistry | 26 | 14% |
| Engineering | 18 | 10% |
| Nursing and Health Professions | 8 | 4% |
| Business, Management and Accounting | 7 | 4% |
| Other | 30 | 16% |
| Unknown | 59 | 31% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 17 October 2017.
All research outputs
#15,660,793
of 23,885,338 outputs
Outputs from Journal of Medical Systems
#670
of 1,201 outputs
Outputs of similar age
#197,309
of 329,340 outputs
Outputs of similar age from Journal of Medical Systems
#11
of 33 outputs
Altmetric has tracked 23,885,338 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,201 research outputs from this source. They receive a mean Attention Score of 4.6. This one is in the 42nd percentile – i.e., 42% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 329,340 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 33 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 66% of its contemporaries.