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Artificial intelligence can improve decision-making in infection management

Author

Listed:
  • Timothy M. Rawson

    (Imperial College London)

  • Raheelah Ahmad

    (Imperial College London)

  • Christofer Toumazou

    (Imperial College London)

  • Pantelis Georgiou

    (Imperial College London)

  • Alison H. Holmes

    (Imperial College London)

Abstract

Antibiotic resistance is an emerging global danger. Reaching responsible prescribing decisions requires the integration of broad and complex information. Artificial intelligence tools could support decision-making at multiple levels, but building them needs a transparent co-development approach to ensure their adoption upon implementation.

Suggested Citation

  • Timothy M. Rawson & Raheelah Ahmad & Christofer Toumazou & Pantelis Georgiou & Alison H. Holmes, 2019. "Artificial intelligence can improve decision-making in infection management," Nature Human Behaviour, Nature, vol. 3(6), pages 543-545, June.
    • Handle: RePEc:nat:nathum:v:3:y:2019:i:6:d:10.1038_s41562-019-0583-9
    DOI: 10.1038/s41562-019-0583-9
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    Cited by:

    1. Minkyu Shin & Jin Kim & Bas van Opheusden & Thomas L. Griffiths, 2023. "Superhuman Artificial Intelligence Can Improve Human Decision Making by Increasing Novelty," Papers 2303.07462, arXiv.org, revised Apr 2023.

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