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Opportunities and obstacles for deep learning in biology and medicine

Overview of attention for article published in bioRxiv, January 2018
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Citations

dimensions_citation
65 Dimensions

Readers on

mendeley
1175 Mendeley
citeulike
3 CiteULike
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Title
Opportunities and obstacles for deep learning in biology and medicine
Published in
bioRxiv, January 2018
DOI 10.1101/142760
Authors

Ching, Travers, Himmelstein, Daniel S., Beaulieu-Jones, Brett K., Kalinin, Alexandr A., Do, Brian T., Way, Gregory P., Ferrero, Enrico, Agapow, Paul-Michael, Zietz, Michael, Hoffman, Michael M., Xie, Wei, Rosen, Gail L., Lengerich, Benjamin J., Israeli, Johnny, Lanchantin, Jack, Woloszynek, Stephen, Carpenter, Anne E., Shrikumar, Avanti, Xu, Jinbo, Cofer, Evan M., Lavender, Christopher A., Turaga, Srinivas C., Alexandari, Amr M., Lu, Zhiyong, Harris, David J., DeCaprio, Dave, Qi, Yanjun, Kundaje, Anshul, Peng, Yifan, Wiley, Laura K., Segler, Marwin H.S., Boca, Simina M., Swamidass, S. Joshua, Huang, Austin, Gitter, Anthony, Greene, Casey S., Travers Ching, Daniel S. Himmelstein, Brett K. Beaulieu-Jones, Alexandr A. Kalinin, Brian T. Do, Gregory P. Way, Enrico Ferrero, Paul-Michael Agapow, Michael Zietz, Michael M. Hoffman, Wei Xie, Gail L. Rosen, Benjamin J. Lengerich, Johnny Israeli, Jack Lanchantin, Stephen Woloszynek, Anne E. Carpenter, Avanti Shrikumar, Jinbo Xu, Evan M. Cofer, Christopher A. Lavender, Srinivas C. Turaga, Amr M. Alexandari, Zhiyong Lu, David J. Harris, Dave DeCaprio, Yanjun Qi, Anshul Kundaje, Yifan Peng, Laura K. Wiley, Marwin H.S. Segler, Simina M. Boca, S. Joshua Swamidass, Austin Huang, Anthony Gitter, Casey S. Greene

Twitter Demographics

The data shown below were collected from the profiles of 897 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 1,175 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 <1%
United Kingdom 2 <1%
Canada 2 <1%
Uruguay 1 <1%
China 1 <1%
Spain 1 <1%
Germany 1 <1%
Unknown 1165 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 291 25%
Researcher 266 23%
Student > Master 146 12%
Student > Bachelor 90 8%
Other 72 6%
Other 182 15%
Unknown 128 11%
Readers by discipline Count As %
Computer Science 300 26%
Agricultural and Biological Sciences 186 16%
Biochemistry, Genetics and Molecular Biology 182 15%
Engineering 94 8%
Medicine and Dentistry 64 5%
Other 189 16%
Unknown 160 14%

Attention Score in Context

This research output has an Altmetric Attention Score of 565. 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 09 July 2020.
All research outputs
#21,161
of 17,178,619 outputs
Outputs from bioRxiv
#139
of 113,721 outputs
Outputs of similar age
#651
of 276,897 outputs
Outputs of similar age from bioRxiv
#2
of 2,814 outputs
Altmetric has tracked 17,178,619 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 113,721 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.8. This one has done particularly well, scoring higher than 99% 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 276,897 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 2,814 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.