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Non-invasive risk prediction models in identifying undiagnosed type 2 diabetes or predicting future incident cases in the Iranian population

Lotfaliany, Mojtaba, Hadaegh, Farzad, Asgari, Samaneh, Mansournia, Mohammad Ali, Azizi, Fereidoun, Oldenburg, Brian and Khalili, Davood 2019, Non-invasive risk prediction models in identifying undiagnosed type 2 diabetes or predicting future incident cases in the Iranian population, Archives of Iranian medicine, vol. 22, no. 3, pp. 116-124.

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Title Non-invasive risk prediction models in identifying undiagnosed type 2 diabetes or predicting future incident cases in the Iranian population
Author(s) Lotfaliany, MojtabaORCID iD for Lotfaliany, Mojtaba orcid.org/0000-0001-6594-9004
Hadaegh, Farzad
Asgari, Samaneh
Mansournia, Mohammad Ali
Azizi, Fereidoun
Oldenburg, Brian
Khalili, Davood
Journal name Archives of Iranian medicine
Volume number 22
Issue number 3
Start page 116
End page 124
Total pages 9
Publisher Academy of Medical Sciences of I.R. Iran
Place of publication Tehran, Iran
Publication date 2019-03
ISSN 1029-2977
1735-3947
Keyword(s) Science & Technology
Life Sciences & Biomedicine
Medicine, General & Internal
General & Internal Medicine
High risk individuals
Non-invasive risk prediction models
Screening methods
Type 2 diabetes
Language eng
Indigenous content off
Field of Research 1103 Clinical Sciences
HERDC Research category C1 Refereed article in a scholarly journal
Free to Read? Yes
Persistent URL http://hdl.handle.net/10536/DRO/DU:30144249

Document type: Journal Article
Collections: Faculty of Health
School of Medicine
Open Access Collection
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Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.