AIMC Topic: Hypoglycemic Agents

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Time for Using Machine Learning for Dose Guidance in Titration of People With Type 2 Diabetes? A Systematic Review of Basal Insulin Dose Guidance.

Journal of diabetes science and technology
BACKGROUND: Real-world studies of people with type 2 diabetes (T2D) have shown insufficient dose adjustment during basal insulin titration in clinical practice leading to suboptimal treatment. Thus, 60% of people with T2D treated with insulin do not ...

Causal deep learning reveals the comparative effectiveness of antihyperglycemic treatments in poorly controlled diabetes.

Nature communications
Type-2 diabetes is associated with severe health outcomes, the effects of which are responsible for approximately 1/4 of the total healthcare spending in the United States (US). Current treatment guidelines endorse a massive number of potential anti-...

A Prediction Algorithm for Hypoglycemia Based on Support Vector Machine Using Glucose Level and Electrocardiogram.

Journal of medical systems
A prediction algorithm for hypoglycemic events is proposed using glucose levels and electrocardiogram (ECG) with support vector machine (SVM). We extracted the corrected QT interval and five heart rate variability parameters from the ECG, along with ...

Mulberry leaves ameliorate diabetes via regulating metabolic profiling and AGEs/RAGE and p38 MAPK/NF-κB pathway.

Journal of ethnopharmacology
ETHNOPHARMACOLOGICAL RELEVANCE: Mulberry leaves have been used as traditional hypoglycemic medicine-food plant for thousand years in China. According to traditional Chinese medicine theory, type 2 diabetes mellitus (T2DM) belongs to the category of X...

Application of Machine Learning to Assess Interindividual Variability in Rapid-Acting Insulin Responses After Subcutaneous Injection in People With Type 1 Diabetes.

Canadian journal of diabetes
OBJECTIVES: Circulating insulin concentrations mediate vascular-inflammatory and prothrombotic factors. However, it is unknown whether interindividual differences in circulating insulin levels are associated with different inflammatory and prothrombo...

Generalizability of heterogeneous treatment effects based on causal forests applied to two randomized clinical trials of intensive glycemic control.

Annals of epidemiology
Purpose Machine learning is an attractive tool for identifying heterogeneous treatment effects (HTE) of interventions but generalizability of machine learning derived HTE remains unclear. We examined generalizability of HTE detected using causal fore...

Modern computational intelligence based drug repurposing for diabetes epidemic.

Diabetes & metabolic syndrome
BACKGROUND AND AIM: Objectives are to explore recent advances in discovery of new antidiabetic agents using repurposing strategies and to discuss modern technologies used for drug repurposing highlighting diabetic specific web portal.

A novel artificial intelligence protocol to investigate potential leads for diabetes mellitus.

Molecular diversity
Dipeptidyl peptidase-4 (DPP4) is highly participated in regulating diabetes mellitus (DM), and inhibitors of DPP4 may act as potential DM drugs. Therefore, we performed a novel artificial intelligence (AI) protocol to screen and validate the potentia...

Systems Approach to Pathogenic Mechanism of Type 2 Diabetes and Drug Discovery Design Based on Deep Learning and Drug Design Specifications.

International journal of molecular sciences
In this study, we proposed a systems biology approach to investigate the pathogenic mechanism for identifying significant biomarkers as drug targets and a systematic drug discovery strategy to design a potential multiple-molecule targeting drug for t...

Bacterial endosymbiont inhabiting leaves and their antioxidant and antidiabetic potential.

Journal of complementary & integrative medicine
OBJECTIVES: Research on endosymbionts is emerging globally and is considered as a potential source of bioactive phytochemicals. The present study examines the antioxidant and antidiabetic of the endophytic crude extract isolated from leaves.