| Title |
Do no harm: a roadmap for responsible machine learning for health care
|
|---|---|
| Published in |
Nature Medicine, August 2019
|
| DOI | 10.1038/s41591-019-0548-6 |
| Pubmed ID | |
| Authors |
Jenna Wiens, Suchi Saria, Mark Sendak, Marzyeh Ghassemi, Vincent X. Liu, Finale Doshi-Velez, Kenneth Jung, Katherine Heller, David Kale, Mohammed Saeed, Pilar N. Ossorio, Sonoo Thadaney-Israni, Anna Goldenberg |
X Demographics
The data shown below were collected from the profiles of 687 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 | 144 | 21% |
| United Kingdom | 70 | 10% |
| Canada | 41 | 6% |
| Spain | 32 | 5% |
| Australia | 16 | 2% |
| Switzerland | 12 | 2% |
| Chile | 12 | 2% |
| Germany | 11 | 2% |
| Netherlands | 10 | 1% |
| Other | 110 | 16% |
| Unknown | 229 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 410 | 60% |
| Scientists | 174 | 25% |
| Practitioners (doctors, other healthcare professionals) | 84 | 12% |
| Science communicators (journalists, bloggers, editors) | 19 | 3% |
Mendeley readers
The data shown below were compiled from readership statistics for 734 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 734 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 119 | 16% |
| Researcher | 114 | 16% |
| Student > Master | 69 | 9% |
| Student > Bachelor | 49 | 7% |
| Other | 45 | 6% |
| Other | 131 | 18% |
| Unknown | 207 | 28% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 130 | 18% |
| Computer Science | 98 | 13% |
| Engineering | 59 | 8% |
| Biochemistry, Genetics and Molecular Biology | 36 | 5% |
| Agricultural and Biological Sciences | 22 | 3% |
| Other | 139 | 19% |
| Unknown | 250 | 34% |
Attention Score in Context
This research output has an Altmetric Attention Score of 708. 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 25 January 2024.
All research outputs
#29,562
of 25,758,695 outputs
Outputs from Nature Medicine
#217
of 9,425 outputs
Outputs of similar age
#564
of 353,378 outputs
Outputs of similar age from Nature Medicine
#2
of 69 outputs
Altmetric has tracked 25,758,695 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 9,425 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 105.6. 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 353,378 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 99% of its contemporaries.
We're also able to compare this research output to 69 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 97% of its contemporaries.