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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Methodological challenges and analytic opportunities for modeling and interpreting Big Healthcare Data
|
|---|---|
| Published in |
Giga Science, February 2016
|
| DOI | 10.1186/s13742-016-0117-6 |
| Pubmed ID | |
| Authors |
Ivo D. Dinov |
| Abstract |
Managing, processing and understanding big healthcare data is challenging, costly and demanding. Without a robust fundamental theory for representation, analysis and inference, a roadmap for uniform handling and analyzing of such complex data remains elusive. In this article, we outline various big data challenges, opportunities, modeling methods and software techniques for blending complex healthcare data, advanced analytic tools, and distributed scientific computing. Using imaging, genetic and healthcare data we provide examples of processing heterogeneous datasets using distributed cloud services, automated and semi-automated classification techniques, and open-science protocols. Despite substantial advances, new innovative technologies need to be developed that enhance, scale and optimize the management and processing of large, complex and heterogeneous data. Stakeholder investments in data acquisition, research and development, computational infrastructure and education will be critical to realize the huge potential of big data, to reap the expected information benefits and to build lasting knowledge assets. Multi-faceted proprietary, open-source, and community developments will be essential to enable broad, reliable, sustainable and efficient data-driven discovery and analytics. Big data will affect every sector of the economy and their hallmark will be 'team science'. |
X Demographics
The data shown below were collected from the profiles of 12 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 4 | 33% |
| Australia | 1 | 8% |
| Canada | 1 | 8% |
| Greece | 1 | 8% |
| Finland | 1 | 8% |
| Hong Kong | 1 | 8% |
| United Kingdom | 1 | 8% |
| Unknown | 2 | 17% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 6 | 50% |
| Scientists | 5 | 42% |
| Science communicators (journalists, bloggers, editors) | 1 | 8% |
Mendeley readers
The data shown below were compiled from readership statistics for 310 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Brazil | 2 | <1% |
| United States | 2 | <1% |
| Ecuador | 1 | <1% |
| Canada | 1 | <1% |
| Switzerland | 1 | <1% |
| Unknown | 303 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 54 | 17% |
| Researcher | 43 | 14% |
| Student > Ph. D. Student | 41 | 13% |
| Student > Doctoral Student | 20 | 6% |
| Student > Bachelor | 17 | 5% |
| Other | 63 | 20% |
| Unknown | 72 | 23% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 80 | 26% |
| Medicine and Dentistry | 31 | 10% |
| Engineering | 24 | 8% |
| Business, Management and Accounting | 14 | 5% |
| Social Sciences | 11 | 4% |
| Other | 72 | 23% |
| Unknown | 78 | 25% |
Attention Score in Context
This research output has an Altmetric Attention Score of 9. 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 25 October 2018.
All research outputs
#4,384,454
of 25,837,817 outputs
Outputs from Giga Science
#747
of 1,176 outputs
Outputs of similar age
#62,765
of 314,708 outputs
Outputs of similar age from Giga Science
#12
of 16 outputs
Altmetric has tracked 25,837,817 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,176 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 21.6. This one is in the 36th percentile – i.e., 36% 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 314,708 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 79% of its contemporaries.
We're also able to compare this research output to 16 others from the same source and published within six weeks on either side of this one. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.