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. Attached Files Name Description MIMEType Size Downloads Title Non-invasive risk prediction models in identifying undiagnosed type 2 diabetes or predicting future incident cases in the Iranian population Author(s) 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 Related Links Link Description Link to full-text (open-access) Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. 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. Versions Version Filter Type Fri, 16 Oct 2020, 08:01:02 EST Sat, 17 Oct 2020, 04:03:11 EST Mon, 19 Oct 2020, 07:02:30 EST Sat, 31 Oct 2020, 01:35:35 EST Tue, 24 Nov 2020, 05:06:51 EST Wed, 25 Nov 2020, 11:15:34 EST Wed, 25 Nov 2020, 11:17:25 EST Wed, 25 Nov 2020, 14:54:25 EST Filtered Full Citation counts:   Cited 2 times in TR Web of Science Cited 1 times in Scopus Search Google Scholar Access Statistics: 28 Abstract Views, 0 File Downloads  -  Detailed Statistics Created: Fri, 16 Oct 2020, 08:01:02 EST

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.