In this section
@article{Rawson:2019:10.1038/s41562-019-0583-9,
author = {Rawson, TM and Ahmad, R and Toumazou, C and Georgiou, P and Holmes, A},
doi = {10.1038/s41562-019-0583-9},
journal = {Nature Human Behaviour},
pages = {543--545},
title = {Artificial intelligence can improve decision-making in infection management},
url = {http://dx.doi.org/10.1038/s41562-019-0583-9},
volume = {3},
year = {2019}
}
TY - JOUR
AB - 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.
AU - Rawson,TM
AU - Ahmad,R
AU - Toumazou,C
AU - Georgiou,P
AU - Holmes,A
DO - 10.1038/s41562-019-0583-9
EP - 545
PY - 2019///
SN - 2397-3374
SP - 543
TI - Artificial intelligence can improve decision-making in infection management
T2 - Nature Human Behaviour
UR - http://dx.doi.org/10.1038/s41562-019-0583-9
UR - http://hdl.handle.net/10044/1/69553
VL - 3
ER -
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