| dc.contributor.author | Russon, CL | |
| dc.contributor.author | Vaughan, N | |
| dc.contributor.author | Pulsford, RM | |
| dc.contributor.author | Andrews, RC | |
| dc.contributor.author | Allen, M | |
| dc.date.accessioned | 2022-06-13T08:12:04Z | |
| dc.date.issued | 2022-08-03 | |
| dc.date.updated | 2022-06-12T08:00:46Z | |
| dc.description.sponsorship | Research England | en_GB |
| dc.identifier.citation | Vol. 65 (supplement 1), p. S324, paper 631 | en_GB |
| dc.identifier.doi | https://doi.org/10.1007/s00125-022-05755-w | |
| dc.identifier.uri | http://hdl.handle.net/10871/129922 | |
| dc.identifier | ORCID: 0000-0001-5038-6560 (Vaughan, Neil) | |
| dc.language.iso | en | en_GB |
| dc.publisher | Springer | en_GB |
| dc.rights.embargoreason | Under embargo until 3 August 2023 in compliance with publisher policy | |
| dc.rights | © 2022 Springer | en_GB |
| dc.title | Glycaemic events during exercise can be effectively predicted with machine learning using only start glucose and duration | en_GB |
| dc.type | Conference paper | en_GB |
| dc.date.available | 2022-06-13T08:12:04Z | |
| exeter.location | Stockholm, Sweden | |
| dc.description | This is the author accepted manuscript. The final version is available from Springer via the DOI in this record | en_GB |
| dc.description | Oral presentation at 58th EASD Annual Meeting, Stockholm, Sweden, 19 - 23 September 2022 | |
| dc.identifier.journal | Diabetologia | |
| dc.rights.uri | http://www.rioxx.net/licenses/all-rights-reserved | en_GB |
| dcterms.dateAccepted | 2022-05-25 | |
| rioxxterms.version | AM | en_GB |
| rioxxterms.licenseref.startdate | 2022-05-25 | |
| rioxxterms.type | Conference Paper/Proceeding/Abstract | en_GB |
| refterms.dateFCD | 2022-06-12T08:00:52Z | |
| refterms.versionFCD | AM | |
| refterms.panel | A | en_GB |
| pubs.name-of-conference | European Association for the Study of Diabetes (EASD) | |
