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X Demographics
Mendeley readers
Title |
A non-invasive artificial intelligence approach for the prediction of human blastocyst ploidy: a retrospective model development and validation study
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Published in |
The Lancet Digital Health, January 2023
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DOI | 10.1016/s2589-7500(22)00213-8 |
Pubmed ID | |
Authors |
Josue Barnes, Matthew Brendel, Vianne R Gao, Suraj Rajendran, Junbum Kim, Qianzi Li, Jonas E Malmsten, Jose T Sierra, Pantelis Zisimopoulos, Alexandros Sigaras, Pegah Khosravi, Marcos Meseguer, Qiansheng Zhan, Zev Rosenwaks, Olivier Elemento, Nikica Zaninovic, Iman Hajirasouliha |
X Demographics
The data shown below were collected from the profiles of 23 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 | 8 | 35% |
United Kingdom | 2 | 9% |
South Africa | 1 | 4% |
Indonesia | 1 | 4% |
Germany | 1 | 4% |
Unknown | 10 | 43% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 13 | 57% |
Scientists | 5 | 22% |
Practitioners (doctors, other healthcare professionals) | 3 | 13% |
Science communicators (journalists, bloggers, editors) | 2 | 9% |
Mendeley readers
The data shown below were compiled from readership statistics for 75 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 75 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 11 | 15% |
Researcher | 7 | 9% |
Student > Bachelor | 5 | 7% |
Other | 5 | 7% |
Student > Master | 4 | 5% |
Other | 10 | 13% |
Unknown | 33 | 44% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 12 | 16% |
Engineering | 9 | 12% |
Computer Science | 4 | 5% |
Biochemistry, Genetics and Molecular Biology | 4 | 5% |
Nursing and Health Professions | 2 | 3% |
Other | 8 | 11% |
Unknown | 36 | 48% |