AIMC Topic: Diabetes Mellitus, Type 2

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Mechanistic machine learning: how data assimilation leverages physiologic knowledge using Bayesian inference to forecast the future, infer the present, and phenotype.

Journal of the American Medical Informatics Association : JAMIA
We introduce data assimilation as a computational method that uses machine learning to combine data with human knowledge in the form of mechanistic models in order to forecast future states, to impute missing data from the past by smoothing, and to i...

Cardiorenal Outcomes in the CANVAS, DECLARE-TIMI 58, and EMPA-REG OUTCOME Trials: A Systematic Review.

Reviews in cardiovascular medicine
In this systematic review, we sought to summarize the 3 recent sodium-glucose cotransporter 2 inhibitor (SGLT2i) trials (Dapagliflozin Effect on CardiovasculAR Events (DECLARE-TIMI 58), Canagliflozin Cardiovascular Assessment Study (CANVAS) Program, ...

Considerations for automated machine learning in clinical metabolic profiling: Altered homocysteine plasma concentration associated with metformin exposure.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
With the maturation of metabolomics science and proliferation of biobanks, clinical metabolic profiling is an increasingly opportunistic frontier for advancing translational clinical research. Automated Machine Learning (AutoML) approaches provide ex...

Fruit Wines Inhibitory Activity Against α-Glucosidase.

Current pharmaceutical biotechnology
BACKGROUND: Fruit wines are well known for their profound health-promoting properties including both enzyme activations and inhibitions. They may act preventive in regard to diabetes melitus and other chronic diseases.

Applying Risk Models on Patients with Unknown Predictor Values: An Incremental Learning Approach.

Studies in health technology and informatics
In clinical practice, many patients may have unknown or missing values for some predictors, causing that the developed risk models cannot be directly applied on these patients. In this paper, we propose an incremental learning approach to apply a dev...

Pattern and predictors of urine protein excretion among patients with type 2 diabetes attending a single tertiary hospital in Lagos, Nigeria.

Saudi journal of kidney diseases and transplantation : an official publication of the Saudi Center for Organ Transplantation, Saudi Arabia
Testing for proteinuria is used to screen for diabetic nephropathy. However, significant proportion of diabetics has normal urine protein excretion despite impaired renal function. We aimed to determine the factors predicting increased urine protein ...

Lactate levels and risk of lactic acidosis with metformin in diabetic kidney disease patients.

Saudi journal of kidney diseases and transplantation : an official publication of the Saudi Center for Organ Transplantation, Saudi Arabia
Metformin as an oral antidiabetic drug (OAD) is not recommended in renal failure due to the presumed risk of lactic acidosis though it has advantages in cardiovascular protection with a low risk of hypoglycemia. Few studies have measured lactic acid ...

Comparison of machine-learning algorithms to build a predictive model for detecting undiagnosed diabetes - ELSA-Brasil: accuracy study.

Sao Paulo medical journal = Revista paulista de medicina
CONTEXT AND OBJECTIVE:: Type 2 diabetes is a chronic disease associated with a wide range of serious health complications that have a major impact on overall health. The aims here were to develop and validate predictive models for detecting undiagnos...

Renal Function in Type 2 Diabetes Following Gastric Bypass.

Deutsches Arzteblatt international
BACKGROUND: Metabolic surgery for obese patients with type 2 diabetes (T2D) yields short- and long-term remission rates of 60-90%. Its effects on diabetesassociated complications such as neuropathy and nephropathy have not been well studied to date. ...