The University of Southampton
University of Southampton Institutional Repository

Development of machine learning models to predict risk of pathology or need for intervention amongst adult patients undergoing colonoscopy

Development of machine learning models to predict risk of pathology or need for intervention amongst adult patients undergoing colonoscopy
Development of machine learning models to predict risk of pathology or need for intervention amongst adult patients undergoing colonoscopy
Stammers, M
9350205a-3938-4d75-8e86-233a38cdbb0e
Thayalasekaran, S
faeaf07c-7303-46ae-a400-c06754712695
Abdelrahim, M
10ed60d7-1296-4d87-a1b5-a3d5b0643cd2
Bhandari, P
5d6f89f0-a69d-48d7-b182-95e7f400e1c9
Stammers, M
9350205a-3938-4d75-8e86-233a38cdbb0e
Thayalasekaran, S
faeaf07c-7303-46ae-a400-c06754712695
Abdelrahim, M
10ed60d7-1296-4d87-a1b5-a3d5b0643cd2
Bhandari, P
5d6f89f0-a69d-48d7-b182-95e7f400e1c9

Stammers, M, Thayalasekaran, S, Abdelrahim, M and Bhandari, P (2020) Development of machine learning models to predict risk of pathology or need for intervention amongst adult patients undergoing colonoscopy. ESGE Days, Dublin, Ireland. 23 - 25 Apr 2020. (doi:10.1055/s-0040-1704082).

Record type: Conference or Workshop Item (Paper)

This record has no associated files available for download.

More information

Published date: 23 April 2020
Venue - Dates: ESGE Days, Dublin, Ireland, 2020-04-23 - 2020-04-25

Identifiers

Local EPrints ID: 481115
URI: http://eprints.soton.ac.uk/id/eprint/481115
PURE UUID: e18e0457-a61b-45dd-8a6e-065819b555f1

Catalogue record

Date deposited: 15 Aug 2023 16:54
Last modified: 17 Mar 2024 02:43

Export record

Altmetrics

Contributors

Author: M Stammers
Author: S Thayalasekaran
Author: M Abdelrahim
Author: P Bhandari

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

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.

×