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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Explainability for artificial intelligence in healthcare: a multidisciplinary perspective
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, November 2020
|
| DOI | 10.1186/s12911-020-01332-6 |
| Pubmed ID | |
| Authors |
Julia Amann, Alessandro Blasimme, Effy Vayena, Dietmar Frey, Vince I. Madai |
X Demographics
The data shown below were collected from the profiles of 37 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 5 | 14% |
| Austria | 3 | 8% |
| India | 3 | 8% |
| Ghana | 2 | 5% |
| United States | 2 | 5% |
| Norway | 2 | 5% |
| Belgium | 2 | 5% |
| United Kingdom | 1 | 3% |
| South Africa | 1 | 3% |
| Other | 3 | 8% |
| Unknown | 13 | 35% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 26 | 70% |
| Scientists | 7 | 19% |
| Science communicators (journalists, bloggers, editors) | 3 | 8% |
| Practitioners (doctors, other healthcare professionals) | 1 | 3% |
Mendeley readers
The data shown below were compiled from readership statistics for 920 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 920 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 99 | 11% |
| Student > Master | 84 | 9% |
| Researcher | 74 | 8% |
| Student > Bachelor | 61 | 7% |
| Student > Doctoral Student | 36 | 4% |
| Other | 133 | 14% |
| Unknown | 433 | 47% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 124 | 13% |
| Medicine and Dentistry | 73 | 8% |
| Engineering | 53 | 6% |
| Business, Management and Accounting | 28 | 3% |
| Nursing and Health Professions | 24 | 3% |
| Other | 158 | 17% |
| Unknown | 460 | 50% |
Attention Score in Context
This research output has an Altmetric Attention Score of 35. 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 17 February 2024.
All research outputs
#1,140,604
of 25,383,225 outputs
Outputs from BMC Medical Informatics and Decision Making
#42
of 2,139 outputs
Outputs of similar age
#30,642
of 524,813 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#1
of 56 outputs
Altmetric has tracked 25,383,225 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,139 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.3. This one has done particularly well, scoring higher than 98% 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 524,813 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 94% of its contemporaries.
We're also able to compare this research output to 56 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 99% of its contemporaries.