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A non-invasive artificial intelligence approach for the prediction of human blastocyst ploidy: a retrospective model development and validation study

Overview of attention for article published in The Lancet Digital Health, January 2023
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14 news outlets
blogs
2 blogs
twitter
23 X users

Citations

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21 Dimensions

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75 Mendeley
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Title
A non-invasive artificial intelligence approach for the prediction of human blastocyst ploidy: a retrospective model development and validation study
Published in
The Lancet Digital Health, January 2023
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

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.
Mendeley readers

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%