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Interpretable multimodal deep learning for real-time pan-tissue pan-disease pathology search on social media

Overview of attention for article published in bioRxiv, August 2018
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153 X users

Citations

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Readers on

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15 Mendeley
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Title
Interpretable multimodal deep learning for real-time pan-tissue pan-disease pathology search on social media
Published in
bioRxiv, August 2018
DOI 10.1101/396663
Authors

Andrew J. Schaumberg, Wendy C. Juarez-Nicanor, Sarah J. Choudhury, Laura G. Pastrián, Bobbi S. Pritt, Mario Prieto Pozuelo, Ricardo Sotillo Sánchez, Khanh Ho, Nusrat Zahra, Betul Duygu Sener, Stephen Yip, Bin Xu, Srinivas Rao Annavarapu, Aurélien Morini, Karra A. Jones, Kathia Rosado-Orozco, Sanjay Mukhopadhyay, Carlos Miguel, Hongyu Yang, Yale Rosen, Rola H. Ali, Olaleke O. Folaranmi, Jerad M. Gardner, Corina Rusu, Celina Stayerman, John Gross, Dauda E. Suleiman, S. Joseph Sirintrapun, Mariam Aly, Thomas J. Fuchs

X Demographics

X Demographics

The data shown below were collected from the profiles of 153 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 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 15 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 13%
Student > Ph. D. Student 2 13%
Student > Bachelor 1 7%
Student > Master 1 7%
Professor > Associate Professor 1 7%
Other 0 0%
Unknown 8 53%
Readers by discipline Count As %
Agricultural and Biological Sciences 2 13%
Nursing and Health Professions 1 7%
Mathematics 1 7%
Psychology 1 7%
Social Sciences 1 7%
Other 0 0%
Unknown 9 60%