| Title |
Evaluation of Explainable Deep Learning Methods for Ophthalmic Diagnosis
|
|---|---|
| Published in |
Clinical Ophthalmology, June 2021
|
| DOI | 10.2147/opth.s312236 |
| Pubmed ID | |
| Authors |
Amitojdeep Singh, Janarthanam Jothi Balaji, Mohammed Abdul Rasheed, Varadharajan Jayakumar, Rajiv Raman, Vasudevan Lakshminarayanan |
X Demographics
The data shown below were collected from the profiles of 8 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 | 4 | 50% |
| Nigeria | 1 | 13% |
| Spain | 1 | 13% |
| France | 1 | 13% |
| Unknown | 1 | 13% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 6 | 75% |
| Scientists | 1 | 13% |
| Practitioners (doctors, other healthcare professionals) | 1 | 13% |
Mendeley readers
The data shown below were compiled from readership statistics for 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 43 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 6 | 14% |
| Student > Ph. D. Student | 5 | 12% |
| Lecturer | 3 | 7% |
| Student > Doctoral Student | 3 | 7% |
| Student > Bachelor | 2 | 5% |
| Other | 6 | 14% |
| Unknown | 18 | 42% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 10 | 23% |
| Engineering | 3 | 7% |
| Nursing and Health Professions | 2 | 5% |
| Medicine and Dentistry | 2 | 5% |
| Business, Management and Accounting | 1 | 2% |
| Other | 5 | 12% |
| Unknown | 20 | 47% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 02 February 2022.
All research outputs
#8,270,333
of 25,392,582 outputs
Outputs from Clinical Ophthalmology
#777
of 3,714 outputs
Outputs of similar age
#172,792
of 459,810 outputs
Outputs of similar age from Clinical Ophthalmology
#27
of 139 outputs
Altmetric has tracked 25,392,582 research outputs across all sources so far. This one has received more attention than most of these and is in the 66th percentile.
So far Altmetric has tracked 3,714 research outputs from this source. They receive a mean Attention Score of 4.9. This one has done well, scoring higher than 78% 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 459,810 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 61% of its contemporaries.
We're also able to compare this research output to 139 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 79% of its contemporaries.