| Title |
Deep learning, computer-aided radiography reading for tuberculosis: a diagnostic accuracy study from a tertiary hospital in India
|
|---|---|
| Published in |
Scientific Reports, January 2020
|
| DOI | 10.1038/s41598-019-56589-3 |
| Pubmed ID | |
| Authors |
Madlen Nash, Rajagopal Kadavigere, Jasbon Andrade, Cynthia Amrutha Sukumar, Kiran Chawla, Vishnu Prasad Shenoy, Tripti Pande, Sophie Huddart, Madhukar Pai, Kavitha Saravu |
X Demographics
The data shown below were collected from the profiles of 40 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| India | 6 | 15% |
| United States | 3 | 8% |
| Canada | 3 | 8% |
| United Kingdom | 3 | 8% |
| Panama | 1 | 3% |
| Australia | 1 | 3% |
| Spain | 1 | 3% |
| Germany | 1 | 3% |
| South Africa | 1 | 3% |
| Other | 3 | 8% |
| Unknown | 17 | 43% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 25 | 63% |
| Scientists | 8 | 20% |
| Practitioners (doctors, other healthcare professionals) | 7 | 18% |
Mendeley readers
The data shown below were compiled from readership statistics for 150 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 150 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 19 | 13% |
| Student > Ph. D. Student | 13 | 9% |
| Student > Bachelor | 12 | 8% |
| Other | 11 | 7% |
| Student > Postgraduate | 10 | 7% |
| Other | 35 | 23% |
| Unknown | 50 | 33% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 28 | 19% |
| Computer Science | 14 | 9% |
| Engineering | 10 | 7% |
| Nursing and Health Professions | 8 | 5% |
| Agricultural and Biological Sciences | 5 | 3% |
| Other | 21 | 14% |
| Unknown | 64 | 43% |
Attention Score in Context
This research output has an Altmetric Attention Score of 26. 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 29 March 2022.
All research outputs
#1,378,711
of 24,213,825 outputs
Outputs from Scientific Reports
#13,312
of 131,698 outputs
Outputs of similar age
#34,224
of 464,218 outputs
Outputs of similar age from Scientific Reports
#445
of 4,316 outputs
Altmetric has tracked 24,213,825 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 131,698 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 18.6. This one has done well, scoring higher than 89% 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 464,218 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 4,316 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.