2023, 27 April
Identifiying predictive factors of diabetic ketoac...
The article “Identification of Predictive Factors of Diabetic Ketoacidosis in Type 1 Diabetes Using a Subgroup Discovery Algorithm” was written...
2023, 27 April
Identification of Predictive Factors of Diabetic K...
To identify predictive factors for diabetic ketoacidosis (DKA) by retrospective analysis of registry data and the use of a subgroup discovery algor...
2020, 28 April
Rationale and methodology for a European pooled an...
Type 2 diabetes mellitus (T2DM) is a common and heterogeneous disease. Using advanced analytic approaches to explore real-world data may identify d...
2020, 28 April
Using natural language processing (NLP) to underst...
IDMPS is an international, observational study to assess care practices and clinical profiles of people with diabetes in developing countries.
2019, 18 September
Identification of predictive factors of DKA using ...
Diabetic ketoacidosis (DKA) is a serious complication of type 1 diabetes (T1D), which is difficult to diagnose due to variability in symptoms.
2019, 17 September
Unmet medical needs in people with type 2 diabetes...
Limited data exist on the impact of different insulin therapy regimes on outcomes in people with diabetes. The current study describes the unmet me...
2019, 03 May
Identification of subgroups of patients with Type ...
To investigate the effects of sodium-glucose co-transporter-2 (SGLT2) inhibitors vs. dipeptidyl peptidase-4 (DPP-4) inhibitors on renal function pr...
2018, 03 October
A machine learning algorithm can identify clusters...
Detecting consistent patterns of interest can be performed using data-driven subgroup discovery algorithms. These may be instrumental in exploiting...