Report for: Opportunities and obstacles for deep learning in biology and medicine

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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

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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.

Geographical breakdown

Country	Count	As %
United States	279	31%
United Kingdom	64	7%
Canada	44	5%
Japan	36	4%
India	27	3%
Spain	25	3%
France	24	3%
Germany	23	3%
Australia	14	2%
Other	111	12%
Unknown	250	28%

Demographic breakdown

Type	Count	As %
Members of the public	508	57%
Scientists	363	40%
Practitioners (doctors, other healthcare professionals)	17	2%
Science communicators (journalists, bloggers, editors)	5	<1%
Unknown	4	<1%

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

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.

Opportunities and obstacles for deep learning in biology and medicine

About this Attention Score

Mentioned by

Citations

Readers on

Twitter Demographics

Geographical breakdown

Demographic breakdown

Mendeley readers

Geographical breakdown

Demographic breakdown

Attention Score in Context