| Title |
Performance of a Deep Neural Network Algorithm Based on a Small Medical Image Dataset: Incremental Impact of 3D-to-2D Reformation Combined with Novel Data Augmentation, Photometric Conversion, or Transfer Learning
|
|---|---|
| Published in |
Journal of Imaging Informatics in Medicine, October 2019
|
| DOI | 10.1007/s10278-019-00267-3 |
| Pubmed ID | |
| Authors |
Vikash Gupta, Mutlu Demirer, Matthew Bigelow, Kevin J. Little, Sema Candemir, Luciano M. Prevedello, Richard D. White, Thomas P. O’Donnell, Michael Wels, Barbaros S. Erdal |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Netherlands | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 50% |
| Practitioners (doctors, other healthcare professionals) | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 33 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 4 | 12% |
| Lecturer | 3 | 9% |
| Student > Bachelor | 3 | 9% |
| Student > Ph. D. Student | 3 | 9% |
| Student > Master | 2 | 6% |
| Other | 3 | 9% |
| Unknown | 15 | 45% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 6 | 18% |
| Nursing and Health Professions | 2 | 6% |
| Mathematics | 1 | 3% |
| Business, Management and Accounting | 1 | 3% |
| Biochemistry, Genetics and Molecular Biology | 1 | 3% |
| Other | 3 | 9% |
| Unknown | 19 | 58% |
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 19 October 2019.
All research outputs
#20,838,437
of 25,604,262 outputs
Outputs from Journal of Imaging Informatics in Medicine
#67
of 83 outputs
Outputs of similar age
#281,200
of 369,650 outputs
Outputs of similar age from Journal of Imaging Informatics in Medicine
#1
of 1 outputs
Altmetric has tracked 25,604,262 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 83 research outputs from this source. They receive a mean Attention Score of 4.2. This one is in the 10th percentile – i.e., 10% 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 369,650 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them