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Cardiovascular medicine
Protocol
A new and automated risk prediction of coronary artery disease using clinical endpoints and medical imaging-derived patient-specific insights: protocol for the retrospective GeoCAD cohort study

Authors

  • Dona Adikari Faculty of Medicine, The University of New South Wales, Sydney, New South Wales, AustraliaCardiology Department, The Prince of Wales Hospital, Sydney, New South Wales, Australia PubMed articlesGoogle scholar articles
  • Ramtin Gharleghi School of Mechanical and Manufacturing Engineering, The University of New South Wales, Sydney, New South Wales, Australia PubMed articlesGoogle scholar articles
  • Shisheng Zhang School of Mechanical and Manufacturing Engineering, The University of New South Wales, Sydney, New South Wales, Australia PubMed articlesGoogle scholar articles
  • Louisa Jorm Centre for Big Data Research in Health, The University of New South Wales, Sydney, New South Wales, Australia PubMed articlesGoogle scholar articles
  • Arcot Sowmya School of Computer Science and Engineering, The University of New South Wales, Sydney, New South Wales, Australia PubMed articlesGoogle scholar articles
  • Daniel Moses School of Computer Science and Engineering, The University of New South Wales, Sydney, New South Wales, AustraliaDepartment of Medical Imaging, The Prince of Wales Hospital, Sydney, New South Wales, Australia PubMed articlesGoogle scholar articles
  • Sze-Yuan Ooi Faculty of Medicine, The University of New South Wales, Sydney, New South Wales, AustraliaCardiology Department, The Prince of Wales Hospital, Sydney, New South Wales, Australia PubMed articlesGoogle scholar articles
  • Susann Beier School of Mechanical and Manufacturing Engineering, The University of New South Wales, Sydney, New South Wales, Australia PubMed articlesGoogle scholar articles
  1. Correspondence to Dr Dona Adikari; dona.adikari{at}unsw.edu.au
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Citation

Adikari D, Gharleghi R, Zhang S, et al
A new and automated risk prediction of coronary artery disease using clinical endpoints and medical imaging-derived patient-specific insights: protocol for the retrospective GeoCAD cohort study
BMJ Open 2022;12:e054881. doi: 10.1136/bmjopen-2021-054881

Publication history

  • Received June 26, 2021
  • Accepted June 5, 2022
  • First published June 20, 2022.
Online issue publication 
August 02, 2023
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© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. http://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.