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Artificial intelligence can improve decision-making in infection management

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Title: Artificial intelligence can improve decision-making in infection management
Authors: Rawson, TM
Ahmad, R
Toumazou, C
Georgiou, P
Holmes, A
Item Type: Journal Article
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.
Issue Date: 25-Mar-2019
Date of Acceptance: 17-Mar-2019
URI: http://hdl.handle.net/10044/1/69553
DOI: https://dx.doi.org/10.1038/s41562-019-0583-9
ISSN: 2397-3374
Publisher: Nature Research
Journal / Book Title: Nature Human Behaviour
Copyright Statement: © 2019 Springer Nature Publishing AG
Sponsor/Funder: National Institute for Health Research
National Institute for Health Research
ESRC
NIHR knowledge mobilisation fellowship
Funder's Grant Number: II-LA-0214-20008
II-LA-0214-20008
KMRF-2015 04 007
Publication Status: Published online
Embargo Date: 2019-09-25
Online Publication Date: 2019-03-25
Appears in Collections:Electrical and Electronic Engineering
Department of Medicine
Faculty of Medicine



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