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Effective resource management using machine learning in medicine: an applied example
  1. Alan Williams1,
  2. Ann-Marie Mekhail2,3,
  3. James Williams4,
  4. Johanna McCord5,
  5. Vanessa Buchan6
  1. 1 Canterbury University, Canterbury District Health Board, Christchurch, New Zealand
  2. 2 Intensive Care Unit, Barts Health NHS Trust, London, UK
  3. 3 School of Medicine, University of Otago, Wellington, New Zealand
  4. 4 Yale University; Canterbury District Health Board, New Haven, Connecticut, USA
  5. 5 Via Innovations, Canterbury District Health Board, Christchurch, New Zealand
  6. 6 Canterbury Health Laboratories, Christchurch, New Zealand
  1. Correspondence to Dr Ann-Marie Mekhail, Intensive Care Unit, Barts Health NHS Trust, Whitechapel E1 1BB, UK; apamekhail{at}gmail.com

Footnotes

  • JMC and VB contributed equally.

  • Contributors AW: Machine learning model design and build, data analysis and manuscript write up. A-MM: Manuscript write up and contexualisation. JM: Project initiation, advice, and review JW: Model validation and manuscript review VB: Project initiation, advice, and review

  • Funding This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.

  • Competing interests AW and JW are co-founders of the software company Isogonal.

  • Provenance and peer review Not commissioned; externally peer reviewed.

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Footnotes

  • JMC and VB contributed equally.

  • Contributors AW: Machine learning model design and build, data analysis and manuscript write up. A-MM: Manuscript write up and contexualisation. JM: Project initiation, advice, and review JW: Model validation and manuscript review VB: Project initiation, advice, and review

  • Funding This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.

  • Competing interests AW and JW are co-founders of the software company Isogonal.

  • Provenance and peer review Not commissioned; externally peer reviewed.

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