Hypoglycemic Agents

Parental perspectives following the implementation of advanced hybrid closed-loop therapy in children and adolescents with type 1 diabetes and elevated glycaemia.

Diabetic medicine : a journal of the British Diabetic Association 39587412

AIMS: To identify from a parental perspective facilitators and barriers of effective implementation of advanced hybrid closed-loop (AHCL) therapy in children and adolescents with type 1 diabetes (T1D) with elevated glycaemia.

Adolescent Blood Glucose Blood Glucose Self-Monitoring Child Diabetes Mellitus, Type 1 Female Glycated Hemoglobin Glycemic Control Humans Hypoglycemic Agents Insulin Insulin Infusion Systems Male Pancreas, Artificial Parents

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Enhancing severe hypoglycemia prediction in type 2 diabetes mellitus through multi-view co-training machine learning model for imbalanced dataset.

Scientific reports 39349500

Patients with type 2 diabetes mellitus (T2DM) who have severe hypoglycemia (SH) poses a considerable risk of long-term death, especially among the elderly, demanding urgent medical attention. Accurate prediction of SH remains challenging due to its m...

Aged Algorithms Blood Glucose Diabetes Mellitus, Type 2 Electronic Health Records Female Glycated Hemoglobin Humans Hypoglycemia Hypoglycemic Agents Machine Learning Male Middle Aged

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Machine learning algorithms mimicking specialists decision making on initial treatment for people with type 2 diabetes mellitus in Japan diabetes data management study (JDDM76).

Diabetes & metabolic syndrome 39644730

OBJECTIVE: To evaluate whether typical machine learning models that mimic specialists' care can successfully reproduce information, not only on whether to prescribe medications but also which hypoglycemic agents to prescribe as initial treatment for ...

Aged Algorithms Decision Making Diabetes Mellitus, Type 2 Female Follow-Up Studies Humans Hypoglycemic Agents Japan Machine Learning Male Middle Aged Prognosis Specialization

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Development and validation of a machine learning model for predicting drug-drug interactions with oral diabetes medications.

Methods (San Diego, Calif.) 39489198

Diabetes management is often complicated by comorbidities, requiring complex medication regimens that increase the risk of drug-drug interactions (DDIs), potentially compromising treatment outcomes or causing toxicity. Although machine learning (ML) ...

Administration, Oral Diabetes Mellitus Drug Interactions Humans Hypoglycemic Agents Machine Learning

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Deep eutectic solvent-based green extraction of Strychnos potatorum seed phenolics: Process optimization via response surface methodology and artificial neural network.

Talanta 39753082

The current research focused on extraction optimization of bioactive compounds from Strychnos potatorum seeds (SPs) using an eco-friendly glycerol-sodium acetate based deep eutectic solvent (DES). The optimization was accomplished using response surf...

alpha-Amylases Antioxidants Biphenyl Compounds Deep Eutectic Solvents Glycerol Green Chemistry Technology Hypoglycemic Agents Neural Networks, Computer Phenols Picrates Plant Extracts Seeds Sodium Acetate Strychnos

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In silico design of dehydrophenylalanine containing peptide activators of glucokinase using pharmacophore modelling, molecular dynamics and machine learning: implications in type 2 diabetes.

Journal of computer-aided molecular design 39739078

Diabetes represents a significant global health challenge associated with substantial healthcare costs and therapeutic complexities. Current diabetes therapies often entail adverse effects, necessitating the exploration of novel agents. Glucokinase (...

Computer Simulation Diabetes Mellitus, Type 2 Drug Design Enzyme Activators Glucokinase Humans Hypoglycemic Agents Machine Learning Molecular Docking Simulation Molecular Dynamics Simulation Peptides Pharmacophore Phenylalanine

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Modeling the fasting blood glucose response to basal insulin adjustment in type 2 diabetes: An explainable machine learning approach on real-world data.

International journal of medical informatics 39705917

INTRODUCTION: Optimal basal insulin titration for people with type 2 diabetes is vital to effectively reducing the risk of complications. However, a sizeable proportion of people (30-50 %) remain in suboptimal glycemic control six months post-initiat...

Aged Blood Glucose Diabetes Mellitus, Type 2 Fasting Female Humans Hypoglycemic Agents Insulin Machine Learning Male Middle Aged

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Leveraging artificial intelligence and machine learning to accelerate discovery of disease-modifying therapies in type 1 diabetes.

Diabetologia 39694914

Progress in developing therapies for the maintenance of endogenous insulin secretion in, or the prevention of, type 1 diabetes has been hindered by limited animal models, the length and cost of clinical trials, difficulties in identifying individuals...

Animals Artificial Intelligence Diabetes Mellitus, Type 1 Drug Discovery Humans Hypoglycemic Agents Machine Learning

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Early Detection of Dementia in Populations With Type 2 Diabetes: Predictive Analytics Using Machine Learning Approach.

Journal of medical Internet research 39434474

BACKGROUND: The possible association between diabetes mellitus and dementia has raised concerns, given the observed coincidental occurrences.

Aged Aged, 80 and over Dementia Diabetes Mellitus, Type 2 Early Diagnosis Female Humans Hypoglycemic Agents Machine Learning Male Middle Aged Neural Networks, Computer Retrospective Studies Taiwan

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Employing Machine Learning Models to Predict Potential α-Glucosidase Inhibitory Plant Secondary Metabolites Targeting Type-2 Diabetes and Their Validation.

Journal of chemical information and modeling 39352297

The need for new antidiabetic drugs is evident, considering the ongoing global burden of type-2 diabetes mellitus despite notable progress in drug discovery from laboratory research to clinical application. This study aimed to build machine learning ...

alpha-Glucosidases Diabetes Mellitus, Type 2 Glycoside Hydrolase Inhibitors Humans Hypoglycemic Agents Machine Learning Plants Secondary Metabolism

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Parental perspectives following the implementation of advanced hybrid closed-loop therapy in children and adolescents with type 1 diabetes and elevated glycaemia.

Enhancing severe hypoglycemia prediction in type 2 diabetes mellitus through multi-view co-training machine learning model for imbalanced dataset.

Machine learning algorithms mimicking specialists decision making on initial treatment for people with type 2 diabetes mellitus in Japan diabetes data management study (JDDM76).

Development and validation of a machine learning model for predicting drug-drug interactions with oral diabetes medications.

Deep eutectic solvent-based green extraction of Strychnos potatorum seed phenolics: Process optimization via response surface methodology and artificial neural network.

In silico design of dehydrophenylalanine containing peptide activators of glucokinase using pharmacophore modelling, molecular dynamics and machine learning: implications in type 2 diabetes.

Modeling the fasting blood glucose response to basal insulin adjustment in type 2 diabetes: An explainable machine learning approach on real-world data.

Leveraging artificial intelligence and machine learning to accelerate discovery of disease-modifying therapies in type 1 diabetes.

Early Detection of Dementia in Populations With Type 2 Diabetes: Predictive Analytics Using Machine Learning Approach.

Employing Machine Learning Models to Predict Potential α-Glucosidase Inhibitory Plant Secondary Metabolites Targeting Type-2 Diabetes and Their Validation.

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