Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation

Search Page

Filters

My NCBI Filters

Results by year

Table representation of search results timeline featuring number of search results per year.

Year Number of Results
2014 3
2016 2
2021 1
2023 2
2024 1

Text availability

Article attribute

Article type

Publication date

Search Results

7 results

Results by year

Filters applied: . Clear all
Page 1
Effect of metformin (vs. placebo or sulfonylurea) on all-cause and cardiovascular mortality and incident cardiovascular events in patients with diabetes: an umbrella review of systematic reviews with meta-analysis.
Bahardoust M, Mousavi S, Yariali M, Haghmoradi M, Hadaegh F, Khalili D, Delpisheh A. Bahardoust M, et al. J Diabetes Metab Disord. 2023 Oct 11;23(1):27-38. doi: 10.1007/s40200-023-01309-y. eCollection 2024 Jun. J Diabetes Metab Disord. 2023. PMID: 38932855 Review.
Gender differences in change of metabolic syndrome status and its components on all-cause and cause-specific mortalities: Over a decade follow-up study.
Afaghi S, Esmaeili F, Azizi F, Hadaegh F. Afaghi S, et al. Nutr Metab Cardiovasc Dis. 2023 Nov;33(11):2128-2140. doi: 10.1016/j.numecd.2023.07.023. Epub 2023 Jul 20. Nutr Metab Cardiovasc Dis. 2023. PMID: 37580229
Moreover, MetS-persistent women with neither hypertension nor diabetes had increased all-cause mortality risk by 88% (F/M-RHR = 3.99 (1.53-5.58)). Women with stable MetS had excess risk of cancer-mortality by 40% (F/M-RHR = 1.63 (1.02-5.06)). ...Both development and …
Moreover, MetS-persistent women with neither hypertension nor diabetes had increased all-cause mortality risk by 88% (F/M-RHR = 3.99 …
The Impact of Oversampling with SMOTE on the Performance of 3 Classifiers in Prediction of Type 2 Diabetes.
Ramezankhani A, Pournik O, Shahrabi J, Azizi F, Hadaegh F, Khalili D. Ramezankhani A, et al. Med Decis Making. 2016 Jan;36(1):137-44. doi: 10.1177/0272989X14560647. Epub 2014 Dec 1. Med Decis Making. 2016. PMID: 25449060
The original and the oversampled training datasets were used to establish the classification models. Accuracy, sensitivity, specificity, precision, F-measure, and Youden's index were used to evaluated the performance of classifiers in the test dataset. ...
The original and the oversampled training datasets were used to establish the classification models. Accuracy, sensitivity, specificity, pre …
Decision tree-based modelling for identification of potential interactions between type 2 diabetes risk factors: a decade follow-up in a Middle East prospective cohort study.
Ramezankhani A, Hadavandi E, Pournik O, Shahrabi J, Azizi F, Hadaegh F. Ramezankhani A, et al. BMJ Open. 2016 Dec 1;6(12):e013336. doi: 10.1136/bmjopen-2016-013336. BMJ Open. 2016. PMID: 27909038 Free PMC article.
The performances of the models were assessed using sensitivity, specificity, area under the ROC curve (AUC), geometric mean (G-Mean) and F-Measure. PRIMARY OUTCOME MEASURE: T2D was primary outcome which defined if fasting plasma glucose (FPG) was 7 mmol/L or if the 2h-PCPG …
The performances of the models were assessed using sensitivity, specificity, area under the ROC curve (AUC), geometric mean (G-Mean) and …
Applying decision tree for identification of a low risk population for type 2 diabetes. Tehran Lipid and Glucose Study.
Ramezankhani A, Pournik O, Shahrabi J, Khalili D, Azizi F, Hadaegh F. Ramezankhani A, et al. Diabetes Res Clin Pract. 2014 Sep;105(3):391-8. doi: 10.1016/j.diabres.2014.07.003. Epub 2014 Jul 18. Diabetes Res Clin Pract. 2014. PMID: 25085758
The overall classification accuracy was 90.5%, with 31.1% sensitivity, 97.9% specificity; and for the subjects without diabetes, precision and f-measure were 92% and 0.95, respectively. The identified variables included fasting plasma glucose, body mass index, triglyceride …
The overall classification accuracy was 90.5%, with 31.1% sensitivity, 97.9% specificity; and for the subjects without diabetes, precision a …