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Mendeley readers
Attention Score in Context
| Title |
Performance Evaluation of Algorithms for the Classification of Metabolic 1H NMR Fingerprints
|
|---|---|
| Published in |
Journal of Proteome Research, November 2012
|
| DOI | 10.1021/pr3009034 |
| Pubmed ID | |
| Authors |
Jochen Hochrein, Matthias S. Klein, Helena U. Zacharias, Juan Li, Gene Wijffels, Horst Joachim Schirra, Rainer Spang, Peter J. Oefner, Wolfram Gronwald |
| Abstract |
Nontargeted metabolite fingerprinting is increasingly applied to biomedical classification. The choice of classification algorithm may have a considerable impact on outcome. In this study, employing nested cross-validation for assessing predictive performance, six binary classification algorithms in combination with different strategies for data-driven feature selection were systematically compared on five data sets of urine, serum, plasma, and milk one-dimensional fingerprints obtained by proton nuclear magnetic resonance (NMR) spectroscopy. Support Vector Machines and Random Forests combined with t-score-based feature filtering performed well on most data sets, whereas the performance of the other tested methods varied between data sets. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Cuba | 1 | 2% |
| Colombia | 1 | 2% |
| Germany | 1 | 2% |
| Unknown | 48 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 15 | 29% |
| Student > Ph. D. Student | 8 | 16% |
| Student > Master | 5 | 10% |
| Student > Doctoral Student | 5 | 10% |
| Student > Postgraduate | 4 | 8% |
| Other | 8 | 16% |
| Unknown | 6 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 14 | 27% |
| Medicine and Dentistry | 9 | 18% |
| Agricultural and Biological Sciences | 8 | 16% |
| Biochemistry, Genetics and Molecular Biology | 4 | 8% |
| Computer Science | 3 | 6% |
| Other | 7 | 14% |
| Unknown | 6 | 12% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 12 November 2012.
All research outputs
#20,172,971
of 22,685,926 outputs
Outputs from Journal of Proteome Research
#5,681
of 6,007 outputs
Outputs of similar age
#159,553
of 179,649 outputs
Outputs of similar age from Journal of Proteome Research
#137
of 150 outputs
Altmetric has tracked 22,685,926 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 6,007 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.2. This one is in the 1st percentile – i.e., 1% 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 179,649 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 150 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.