Periodontitis and diabetes
PM Preshaw, SM Bissett - British dental journal, 2019 - nature.com
Periodontitis and diabetes are complex chronic diseases, linked by an established
bidirectional relationship. Risk for periodontitis is increased two to three times in people with …
bidirectional relationship. Risk for periodontitis is increased two to three times in people with …
[HTML][HTML] Risk factors contributing to type 2 diabetes and recent advances in the treatment and prevention
Y Wu, Y Ding, Y Tanaka, W Zhang - International journal of medical …, 2014 - ncbi.nlm.nih.gov
Type 2 diabetes is a serious and common chronic disease resulting from a complex
inheritance-environment interaction along with other risk factors such as obesity and …
inheritance-environment interaction along with other risk factors such as obesity and …
Machine learning tools for long-term type 2 diabetes risk prediction
A steady rise has been observed in the percentage of elderly people who want and are still
able to contribute to society. Therefore, early retirement or exit from the labour market, due to …
able to contribute to society. Therefore, early retirement or exit from the labour market, due to …
Metabolic reprogramming of the intestinal microbiome with functional bile acid changes underlie the development of NAFLD
Autoimmune hepatitis (AIH) is a rare disease of unclear etiology characterized by loss of self‐
tolerance that can lead to liver injury, cirrhosis, and acute liver failure. First‐line treatment …
tolerance that can lead to liver injury, cirrhosis, and acute liver failure. First‐line treatment …
[HTML][HTML] Diagnostic accuracy of the Finnish Diabetes Risk Score (FINDRISC) for undiagnosed T2DM in Peruvian population
Aims To assess the diagnostic accuracy of the Finnish Diabetes Risk Score (FINDRISC) for
undiagnosed T2DM and to compare its performance with the Latin-American FINDRISC (LA …
undiagnosed T2DM and to compare its performance with the Latin-American FINDRISC (LA …
Developing risk prediction models for type 2 diabetes: a systematic review of methodology and reporting
GS Collins, S Mallett, O Omar, LM Yu - BMC medicine, 2011 - Springer
Abstract Background The World Health Organisation estimates that by 2030 there will be
approximately 350 million people with type 2 diabetes. Associated with renal complications …
approximately 350 million people with type 2 diabetes. Associated with renal complications …
Continual updating and monitoring of clinical prediction models: time for dynamic prediction systems?
Clinical prediction models (CPMs) have become fundamental for risk stratification across
healthcare. The CPM pipeline (development, validation, deployment, and impact …
healthcare. The CPM pipeline (development, validation, deployment, and impact …
Machine learning for diabetes clinical decision support: a review
Type 2 diabetes has recently acquired the status of an epidemic silent killer, though it is non-
communicable. There are two main reasons behind this perception of the disease. First, a …
communicable. There are two main reasons behind this perception of the disease. First, a …
Dynamic models to predict health outcomes: current status and methodological challenges
Background Disease populations, clinical practice, and healthcare systems are constantly
evolving. This can result in clinical prediction models quickly becoming outdated and less …
evolving. This can result in clinical prediction models quickly becoming outdated and less …
Logistic regression has similar performance to optimised machine learning algorithms in a clinical setting: application to the discrimination between type 1 and type 2 …
Background There is much interest in the use of prognostic and diagnostic prediction
models in all areas of clinical medicine. The use of machine learning to improve prognostic …
models in all areas of clinical medicine. The use of machine learning to improve prognostic …