Tools for predicting the risk of type 2 diabetes in daily practice

PEH Schwarz, J Li, J Lindstrom… - … and metabolic research, 2009 - thieme-connect.com
The discussion about the diagnosis and treatment of type 2 diabetes–and, more generally,
dysglycaemia–should be framed in terms of a continuum of risk. A variety of tools have been …

Screening for type 2 diabetes: literature review and economic modelling

N Waugh, G Scotland, P McNamee, M Gillett… - HEALTH …, 2007 - emerald.com
Background The National Screening Committee (NSC) is responsible for providing advice
on screening policy to all parts of the UK. A review of policy on screening for type 2 diabetes …

A fusion-based machine learning approach for the prediction of the onset of diabetes

MW Nadeem, HG Goh, V Ponnusamy, I Andonovic… - Healthcare, 2021 - mdpi.com
A growing portfolio of research has been reported on the use of machine learning-based
architectures and models in the domain of healthcare. The development of data-driven …

Intelligent machine learning approach for effective recognition of diabetes in E-healthcare using clinical data

AU Haq, JP Li, J Khan, MH Memon, S Nazir, S Ahmad… - Sensors, 2020 - mdpi.com
Significant attention has been paid to the accurate detection of diabetes. It is a big challenge
for the research community to develop a diagnosis system to detect diabetes in a successful …

Guidelines on diabetes, pre-diabetes, and cardiovascular diseases: executive summary: The Task Force on Diabetes and Cardiovascular Diseases of the European …

L Rydén, E Standl, M Bartnik… - European heart …, 2007 - academic.oup.com
Task Forces, expert groups, or consensus panels. The chosen experts in these writing
panels are asked to provide disclosure statements of all relationships they may have, which …

A European evidence-based guideline for the prevention of type 2 diabetes

B Paulweber, P Valensi, J Lindström… - Hormone and …, 2010 - thieme-connect.com
Background: The prevalence and socioeconomic burden of type 2 diabetes (T2DM) and
associated co-morbidities are rising worldwide. Aims: This guideline provides evidence …

Intelligible support vector machines for diagnosis of diabetes mellitus

N Barakat, AP Bradley… - IEEE transactions on …, 2010 - ieeexplore.ieee.org
Diabetes mellitus is a chronic disease and a major public health challenge worldwide.
According to the International Diabetes Federation, there are currently 246 million diabetic …

Application of support vector machine modeling for prediction of common diseases: the case of diabetes and pre-diabetes

W Yu, T Liu, R Valdez, M Gwinn, MJ Khoury - BMC medical informatics and …, 2010 - Springer
Background We present a potentially useful alternative approach based on support vector
machine (SVM) techniques to classify persons with and without common diseases. We …

Diabetes Risk Calculator: a simple tool for detecting undiagnosed diabetes and pre-diabetes

KE Heikes, DM Eddy, B Arondekar… - Diabetes …, 2008 - Am Diabetes Assoc
OBJECTIVE—The objective of this study was to develop a simple tool for the US population
to calculate the probability that an individual has either undiagnosed diabetes or pre …

Validation of the Finnish diabetes risk score (FINDRISC) questionnaire for screening for undiagnosed type 2 diabetes, dysglycaemia and the metabolic syndrome in …

K Makrilakis, S Liatis, S Grammatikou, D Perrea… - Diabetes & …, 2011 - Elsevier
Aim The present study aimed to validate the Finnish Type 2 Diabetes Risk Score
(FINDRISC) questionnaire for its ability to predict the presence of any glucose homoeostasis …