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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A molecular computational model improves the preoperative diagnosis of thyroid nodules
|
|---|---|
| Published in |
BMC Cancer, September 2012
|
| DOI | 10.1186/1471-2407-12-396 |
| Pubmed ID | |
| Authors |
Sara Tomei, Ivo Marchetti, Katia Zavaglia, Francesca Lessi, Alessandro Apollo, Paolo Aretini, Giancarlo Di Coscio, Generoso Bevilacqua, Chiara Mazzanti |
| Abstract |
Thyroid nodules with indeterminate cytological features on fine needle aspiration (FNA) cytology have a 20% risk of thyroid cancer. The aim of the current study was to determine the diagnostic utility of an 8-gene assay to distinguish benign from malignant thyroid neoplasm. |
X Demographics
The data shown below were collected from the profiles of 4 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 | 1 | 25% |
| Belgium | 1 | 25% |
| Unknown | 2 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 75% |
| Practitioners (doctors, other healthcare professionals) | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 36 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 12 | 33% |
| Other | 4 | 11% |
| Student > Doctoral Student | 3 | 8% |
| Student > Master | 3 | 8% |
| Student > Bachelor | 2 | 6% |
| Other | 7 | 19% |
| Unknown | 5 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 15 | 42% |
| Biochemistry, Genetics and Molecular Biology | 8 | 22% |
| Agricultural and Biological Sciences | 3 | 8% |
| Nursing and Health Professions | 1 | 3% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 3% |
| Other | 2 | 6% |
| Unknown | 6 | 17% |
Attention Score in Context
This research output has an Altmetric Attention Score of 18. 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 30 June 2022.
All research outputs
#1,870,869
of 23,881,329 outputs
Outputs from BMC Cancer
#289
of 8,483 outputs
Outputs of similar age
#11,978
of 170,610 outputs
Outputs of similar age from BMC Cancer
#5
of 98 outputs
Altmetric has tracked 23,881,329 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,483 research outputs from this source. They receive a mean Attention Score of 4.4. This one has done particularly well, scoring higher than 97% of its peers.
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 170,610 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 92% of its contemporaries.
We're also able to compare this research output to 98 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 95% of its contemporaries.