The University of Southampton
×
Filter your search:
University of Southampton Institutional Repository

Clinical AI tools must convey predictive uncertainty for each individual patient

Clinical AI tools must convey predictive uncertainty for each individual patient
Clinical AI tools must convey predictive uncertainty for each individual patient
Artificial intelligence tools usually aim to maximize predictive accuracy, but personalized measures of uncertainty, using new techniques such as conformal prediction, are needed for clinical artificial intelligence to realize its potential and improve human health.
1078-8956
2996-2998
Banerji, Christopher R.S.
1f2450d6-5772-46b5-a913-2333f7b53a2a
Chakraborti, Tapabrata
26a5ab6f-fd15-4be2-bc8b-ed53f8913548
Harbron, Chris
c9053c59-3f33-4842-aead-905f4a5b20ec
MacArthur, Ben D.
2c0476e7-5d3e-4064-81bb-104e8e88bb6b
Banerji, Christopher R.S.
1f2450d6-5772-46b5-a913-2333f7b53a2a
Chakraborti, Tapabrata
26a5ab6f-fd15-4be2-bc8b-ed53f8913548
Harbron, Chris
c9053c59-3f33-4842-aead-905f4a5b20ec
MacArthur, Ben D.
2c0476e7-5d3e-4064-81bb-104e8e88bb6b

Banerji, Christopher R.S., Chakraborti, Tapabrata, Harbron, Chris and MacArthur, Ben D. (2023) Clinical AI tools must convey predictive uncertainty for each individual patient. Nature Medicine, 29 (12), 2996-2998. (doi:10.1038/s41591-023-02562-7).

Record type: Letter

Abstract

Artificial intelligence tools usually aim to maximize predictive accuracy, but personalized measures of uncertainty, using new techniques such as conformal prediction, are needed for clinical artificial intelligence to realize its potential and improve human health.

Text
Nat Med - Accepted Manuscript
Available under License Other.
Download (255kB)

More information

e-pub ahead of print date: 11 October 2023
Published date: December 2023
Learn more about Institute for Life Sciences research Learn more about Mathematical Sciences research Learn more about Institute for Life Sciences research

Identifiers

Local EPrints ID: 484397
URI: http://eprints.soton.ac.uk/id/eprint/484397
DOI: doi:10.1038/s41591-023-02562-7
ISSN: 1078-8956
PURE UUID: 941ca686-1b38-45d2-8fe7-b3e2a40ac079
ORCID for Ben D. MacArthur: ORCID iD orcid.org/0000-0002-5396-9750

Catalogue record

Date deposited: 16 Nov 2023 11:49
Last modified: 11 Apr 2024 04:01

Export record

Altmetrics

Contributors

Author: Christopher R.S. Banerji
Author: Tapabrata Chakraborti
Author: Chris Harbron
Author: Ben D. MacArthur ORCID iD

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Library staff additional information
Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×