Journal article

Reporting of prognostic clinical prediction models based on machine learning methods in oncology needs to be improved

Abstract:: Objective
Evaluate the completeness of reporting of prognostic prediction models developed using machine learning methods in the field of oncology.
Study design and setting
We conducted a systematic review, searching the MEDLINE and Embase databases between 01/01/2019 and 05/09/2019, for non-imaging studies developing a prognostic clinical prediction model using machine learning methods (as defined by primary study authors) in oncology. We us... Expand abstract
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Publication status:: Published

Peer review status:: Peer reviewed

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APA Style

Dhiman, P., Ma, J., Navarro, C. A., Speich, B., Bullock, G., Damen, J. A., Kirtley, S., Hooft, L., Riley, R. D., Van Calster, B., Moons, K. G. M., & Collins, G. S. (2021). Reporting of prognostic clinical prediction models based on machine learning methods in oncology needs to be improved. Journal of Clinical Epidemiology, 138, 60–72.

MLA Style

Dhiman, P., et al. “Reporting of Prognostic Clinical Prediction Models Based on Machine Learning Methods in Oncology Needs to Be Improved.” Journal of Clinical Epidemiology, vol. 138, Elsevier, 2021, pp. 60–72.

Chicago Style

Dhiman, P, J Ma, CA Navarro, B Speich, G Bullock, JA Damen, S Kirtley, et al. 2021. “Reporting of Prognostic Clinical Prediction Models Based on Machine Learning Methods in Oncology Needs to Be Improved.” Journal of Clinical Epidemiology 138: 60–72.
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Files:: Dhiman_et_al_2021_Reporting_of_prognostic.pdf

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Publisher copy:: 10.1016/j.jclinepi.2021.06.024

Authors

+ Dhiman, P More by this author

Role:

Author

+ Ma, J More by this author

Role:

Author

+ Navarro, CA More by this author

Role:

Author

+ Speich, B More by this author

Role:

Author

+ Bullock, G More by this author

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Author

More authors...

Funding

+ Cancer Research UK More from this funder

Grant:

27294

+ National Institute for Health Research More from this funder

Bibliographic Details

Publisher:: Elsevier
Journal:: Journal of Clinical Epidemiology More from this journal
Volume:: 138
Pages:: 60-72
Publication date:: 2021-06-29
Acceptance date:: 2021-06-25
DOI:: 10.1016/j.jclinepi.2021.06.024
EISSN:: 1878-5921
ISSN:: 0895-4356
Pmid:: 34214626

Item Description

Language:: English
Keywords:: prediction

reporting

FFR

machine learning
Pubs id:: 1185873
Local pid:: pubs:1185873
Deposit date:: 2021-10-29

Terms of use

Copyright holder:: Dhiman et al.
Copyright date:: 2021
Rights statement:: ©2021 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)

Licence:: CC Attribution (CC BY)

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