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X Demographics
Mendeley readers
Attention Score in Context
Title |
Considerations in the reliability and fairness audits of predictive models for advance care planning
|
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Published in |
Frontiers in Digital Health, September 2022
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DOI | 10.3389/fdgth.2022.943768 |
Pubmed ID | |
Authors |
Jonathan Lu, Amelia Sattler, Samantha Wang, Ali Raza Khaki, Alison Callahan, Scott Fleming, Rebecca Fong, Benjamin Ehlert, Ron C. Li, Lisa Shieh, Kavitha Ramchandran, Michael F. Gensheimer, Sarah Chobot, Stephen Pfohl, Siyun Li, Kenny Shum, Nitin Parikh, Priya Desai, Briththa Seevaratnam, Melanie Hanson, Margaret Smith, Yizhe Xu, Arjun Gokhale, Steven Lin, Michael A. Pfeffer, Winifred Teuteberg, Nigam H. Shah |
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 | 3 | 38% |
Switzerland | 1 | 13% |
Unknown | 4 | 50% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 6 | 75% |
Practitioners (doctors, other healthcare professionals) | 1 | 13% |
Scientists | 1 | 13% |
Mendeley readers
The data shown below were compiled from readership statistics for 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 33 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 4 | 12% |
Professor | 2 | 6% |
Lecturer > Senior Lecturer | 1 | 3% |
Lecturer | 1 | 3% |
Unspecified | 1 | 3% |
Other | 4 | 12% |
Unknown | 20 | 61% |
Readers by discipline | Count | As % |
---|---|---|
Unspecified | 2 | 6% |
Business, Management and Accounting | 1 | 3% |
Psychology | 1 | 3% |
Social Sciences | 1 | 3% |
Medicine and Dentistry | 1 | 3% |
Other | 1 | 3% |
Unknown | 26 | 79% |
Attention Score in Context
This research output has an Altmetric Attention Score of 14. 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 28 September 2023.
All research outputs
#2,435,491
of 24,717,692 outputs
Outputs from Frontiers in Digital Health
#67
of 740 outputs
Outputs of similar age
#50,547
of 423,976 outputs
Outputs of similar age from Frontiers in Digital Health
#9
of 81 outputs
Altmetric has tracked 24,717,692 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 740 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.7. This one has done particularly well, scoring higher than 91% 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 423,976 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 88% of its contemporaries.
We're also able to compare this research output to 81 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 90% of its contemporaries.