Conference item

Deep learning to detect features of a population of anti-osteoporosis drug users

Publication status:: Published

Peer review status:: Reviewed (other)

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APA Style

Khalid, S., Ali, M., Rijnbeek, P., & Prieto-Alhambra, D. (2018). Deep learning to detect features of a population of anti-osteoporosis drug users. Pharmacoepidemiology and Drug Safety, 27(S2), 345–346.

MLA Style

Khalid, S., et al. “Deep Learning to Detect Features of a Population of Anti-Osteoporosis Drug Users.” Pharmacoepidemiology and Drug Safety, vol. 27, no. S2, Wiley, 2018, pp. 345–46.

Chicago Style

Khalid, S, M Ali, P Rijnbeek, and D Prieto-Alhambra. 2018. “Deep Learning to Detect Features of a Population of Anti-Osteoporosis Drug Users.” In Pharmacoepidemiology and Drug Safety, 27:345–46. Wiley.
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Files:: Abstract for 2018 ISPE Annual Conference 2018_02_01 SK.pdf

(Preview, Accepted manuscript, pdf, 1.2MB, Terms of use)

Publisher copy:: 10.1002/pds.4629

Authors

+ Khalid, S More by this author

Institution:: University of Oxford
Division:: MSD
Department:: NDORMS
Role:: Author
ORCID:: 0000-0002-2845-5731

+ Ali, M More by this author

Institution:: University of Oxford
Division:: Medical Sciences Division
Department:: NDORMS
Role:: Author

+ Rijnbeek, P More by this author

Role:: Author

+ Prieto-Alhambra, D More by this author

Institution:: University of Oxford
Division:: Medical Sciences Division
Department:: NDORMS
Sub department:: CSM
Role:: Author

Publisher:: Wiley
Host title:: Pharmacoepidemiology and Drug Safety
Journal:: Pharmacoepidemiology and Drug Safety More from this journal
Volume:: 27
Issue:: S2
Pages:: 345-346
Publication date:: 2018-08-17
Acceptance date:: 2018-05-30
DOI:: 10.1002/pds.4629
EISSN:: 1099-1557
ISSN:: 1053-8569

Pubs id:: pubs:921785
UUID:: uuid:e0f22ce1-05e8-4f44-85b5-01041aa0a850
Local pid:: pubs:921785
Source identifiers:: 921785
Deposit date:: 2018-10-05

Terms of use

Copyright holder:: Khalid, et al
Copyright date:: 2018
Notes:: Copyright © 2018 The Authors. Pharmacoepidimeology and Drug Safety © 2018 John Wiley & Sons, Ltd. This abstract was presented at the 34th International Conference on Pharmacoepidemiology and Therapeutic Risk Management, August 22-26, 2018, Prague, Czech Republic. This is the accepted manuscript version of the article. The final version is available online from Wiley at: https://doi.org/10.1002/pds.4629

Licence:: Terms and Conditions of Use for Oxford University Research Archive

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