Automated Machine Learning Approaches for Surgery Duration Prediction in Orthopaedics

Rohan Barrowcliff, Thomas Lovegrove, Holger Kunz

Open source

DOI
10.3233/shti260121
Published
2026-05-21
Container
Studies in Health Technology and Informatics
Publisher
IOS Press
Open access
unknown

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BibTeX

@article{allodium:10.3233/shti260121,
  title = {Automated Machine Learning Approaches for Surgery Duration Prediction in Orthopaedics},
  author = {Rohan Barrowcliff and Thomas Lovegrove and Holger Kunz},
  year = {2026},
  journal = {Studies in Health Technology and Informatics},
  doi = {10.3233/shti260121},
  url = {https://doi.org/10.3233/shti260121}
}

RIS

TY  - JOUR
TI  - Automated Machine Learning Approaches for Surgery Duration Prediction in Orthopaedics
AU  - Rohan Barrowcliff
AU  - Thomas Lovegrove
AU  - Holger Kunz
PY  - 2026
JO  - Studies in Health Technology and Informatics
DO  - 10.3233/shti260121
UR  - https://doi.org/10.3233/shti260121
ER  - 

APA

Barrowcliff, R., Lovegrove, T., & Kunz, H. (2026). Automated Machine Learning Approaches for Surgery Duration Prediction in Orthopaedics. Studies in Health Technology and Informatics. https://doi.org/10.3233/shti260121

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