Conference item

Data-driven cluster analysis for identifying groups within users of anti-osteoporosis medication, using real-world primary care data.

Abstract:: Data-driven methods can be used for pattern recognition within a clinical population, enriching the existing analytical tools for clinical data analysis. We clustered anti-osteoporosis drug users with similar risk factors, to better determine the influence of therapy on their fracture risk

Publication status:: Published

Peer review status:: Reviewed (other)

Actions

Email

Email this record

Send the bibliographic details of this record to your email address.

Your Email
Please enter the email address that the record information will be sent to.

-
Your message (optional)
Please add any additional information to be included within the email.
Cite

Cite this record

APA Style

Khalid, S., Ali, M., Silman, A., & Prieto-Alhambra, D. (2017). Data-driven cluster analysis for identifying groups within users of anti-osteoporosis medication, using real-world primary care data. 38th Annual Conference of the International Society for Clinical Biostatistics (ISCB 2017).

MLA Style

Khalid, S., et al. “Data-Driven Cluster Analysis for Identifying Groups within Users of Anti-Osteoporosis Medication, Using Real-World Primary Care Data.” 38th Annual Conference of the International Society for Clinical Biostatistics (ISCB 2017), International Society for Clinical Biostatistics, 2017.

Chicago Style

Khalid, S, M Ali, A Silman, and D Prieto-Alhambra. 2017. “Data-Driven Cluster Analysis for Identifying Groups within Users of Anti-Osteoporosis Medication, Using Real-World Primary Care Data.” In 38th Annual Conference of the International Society for Clinical Biostatistics (ISCB 2017). International Society for Clinical Biostatistics.
Share
Print

Access Document

Files:: Khalid et al, Data-driven cluster analysis for identifying gro...

(Preview, Accepted manuscript, pdf, 212.9KB, Terms of use)

Authors

+ Khalid, S More by this author

Institution:: University of Oxford
Division:: MSD
Department:: NDORMS
Role:: Author

+ Ali, M More by this author

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

+ Silman, A More by this author

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

+ Prieto-Alhambra, D More by this author

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

Publisher:: International Society for Clinical Biostatistics
Host title:: 38th Annual Conference of the International Society for Clinical Biostatistics (ISCB 2017)
Journal:: 38th Annual Conference of the International Society for Clinical Biostatistics (ISCB 2017) More from this journal
Publication date:: 2017-07-01
Acceptance date:: 2017-04-01

Pubs id:: pubs:709985
UUID:: uuid:bb6a7557-f1c1-4816-a8e2-1b868f459583
Local pid:: pubs:709985
Source identifiers:: 709985
Deposit date:: 2018-02-01

Terms of use

Copyright holder:: International Society for Clinical Biostatistics
Copyright date:: 2017
Notes:: © 2017 International Society for Clinical Biostatistics

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

Views and Downloads

About views and downloads

If you are the owner of this record, you can report an update to it here: Report update to this record

TO TOP