| Title |
Machine learning-based quantitative texture analysis of conventional MRI combined with ADC maps for assessment of IDH1 mutation in high-grade gliomas
|
|---|---|
| Published in |
Japanese Journal of Radiology, November 2019
|
| DOI | 10.1007/s11604-019-00902-7 |
| Pubmed ID | |
| Authors |
Deniz Alis, Omer Bagcilar, Yeseren Deniz Senli, Mert Yergin, Cihan Isler, Naci Kocer, Civan Islak, Osman Kizilkilic |
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 % |
|---|---|---|
| Netherlands | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 34 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 6 | 18% |
| Student > Postgraduate | 5 | 15% |
| Student > Ph. D. Student | 2 | 6% |
| Lecturer | 1 | 3% |
| Student > Doctoral Student | 1 | 3% |
| Other | 4 | 12% |
| Unknown | 15 | 44% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 5 | 15% |
| Biochemistry, Genetics and Molecular Biology | 2 | 6% |
| Mathematics | 1 | 3% |
| Business, Management and Accounting | 1 | 3% |
| Nursing and Health Professions | 1 | 3% |
| Other | 5 | 15% |
| Unknown | 19 | 56% |
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 20 November 2019.
All research outputs
#20,590,073
of 23,175,240 outputs
Outputs from Japanese Journal of Radiology
#269
of 368 outputs
Outputs of similar age
#382,878
of 457,319 outputs
Outputs of similar age from Japanese Journal of Radiology
#5
of 9 outputs
Altmetric has tracked 23,175,240 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 368 research outputs from this source. They receive a mean Attention Score of 3.0. 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 457,319 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 9 others from the same source and published within six weeks on either side of this one. This one has scored higher than 4 of them.