TY - JOUR
KW - cancer diagnosis
KW - early detection
KW - electronic health record
KW - machine learning
KW - oesophago-gastric cancer
KW - primary care
KW - risk-assessment
AU - E. Briggs
AU - M. de Kamps
AU - W. Hamilton
AU - O. Johnson
AU - C. McInerney
AU - R. Neal
AD - School of Computing, University of Leeds, Leeds LS2 9JT, UK.
Leeds Institute for Data Analytics, University of Leeds, Leeds LS2 9NL, UK.
The Alan Turing Institute, London NW1 2DB, UK.
Department of Health and Community Sciences, University of Exeter, Exeter EX1 2LU, UK.
Academic Unit of Primary Medical Care, University of Sheffield, Sheffield S10 2TN, UK.
AN - 36291807
BT - Cancers (Basel)
C2 - PMC9600097
DO - 10.3390/cancers14205023
DP - NLM
ET - 2022/10/28
LA - eng
M1 - 20
N1 - 2072-6694
Briggs, Emma
Orcid: 0000-0003-0757-6187
de Kamps, Marc
Orcid: 0000-0001-7162-4425
Hamilton, Willie
Orcid: 0000-0003-1611-1373
Johnson, Owen
Orcid: 0000-0003-3998-541x
McInerney, Ciarán D
Neal, Richard D
EP/S024336/1//Engineering and Physical Sciences Research Council/
Journal Article
Cancers (Basel). 2022 Oct 14;14(20):5023. doi: 10.3390/cancers14205023.
PY - 2022
SN - 2072-6694 (Print)2072-6694
T2 - Cancers (Basel)
TI - Machine Learning for Risk Prediction of Oesophago-Gastric Cancer in Primary Care: Comparison with Existing Risk-Assessment Tools
VL - 14
ER -