Please use this identifier to cite or link to this item:
http://bura.brunel.ac.uk/handle/2438/25861
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Almutairi, E | - |
dc.contributor.author | Abbod, M | - |
dc.date.accessioned | 2023-01-23T18:28:24Z | - |
dc.date.available | 2023-01-23T18:28:24Z | - |
dc.date.issued | 2023 | - |
dc.identifier.citation | Almutairi. E. and Abbod, M. (2023) 'Machine learning methods for diabetes prevalence classification in Saudi Arabia', Modelling, 0 (accepted, in press), pp. 1 - 20. | en_US |
dc.identifier.uri | https://bura.brunel.ac.uk/handle/2438/25861 | - |
dc.description | Data Availability Statement: Data presented in the paper are available on request from 649 the corresponding author M.F.A. | en_US |
dc.description.abstract | Copyright: © 2022 by the authors. | en_US |
dc.description.sponsorship | Unknown | en_US |
dc.format.extent | 1 - 20 | - |
dc.format.medium | Electronic | - |
dc.language.iso | en_US | en_US |
dc.publisher | MDPI AG | en_US |
dc.rights | Copyright: © 2022 by the authors. Submitted for possible open access publication under the terms and con-ditions of the Creative Commons At-tribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). | - |
dc.subject | machine learning | en_US |
dc.subject | diabetes | en_US |
dc.subject | classification | en_US |
dc.title | Machine learning methods for diabetes prevalence classification in Saudi Arabia | en_US |
dc.type | Article | en_US |
dc.relation.isPartOf | Modelling | - |
pubs.publication-status | Accepted | - |
pubs.volume | 0 | - |
dc.rights.holder | The authors | - |
Appears in Collections: | Dept of Electronic and Electrical Engineering Embargoed Research Papers |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
FullText.pdf | Embargoed until publication | 742.56 kB | Adobe PDF | View/Open |
Items in BURA are protected by copyright, with all rights reserved, unless otherwise indicated.