AIMC Topic: Glycated Hemoglobin

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Data-driven diabetes mellitus prediction and management: a comparative evaluation of decision tree classifier and artificial neural network models along with statistical analysis.

Scientific reports Jun 2, 2025
Diabetes Mellitus is a chronic metabolic disorder affecting a substantial global population leading to complications such as retinopathy, nephropathy, neuropathy, foot problems, heart attacks, and strokes if left unchecked. Prompt detection and diagn...
Adult Male Middle Aged Diabetes Mellitus Decision Trees Glycated Hemoglobin Humans Neural Networks, Computer Female Aged
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Predicting diabetes mellitus metabolic goals and chronic complications transitions-analysis based on natural language processing and machine learning models.

PloS one Apr 15, 2025
OBJECTIVE: To estimate Diabetes mellitus (DM) progression at one and two years in terms of glycemic targets and development of complications.
Humans Machine Learning Diabetes Mellitus Natural Language Processing Glycated Hemoglobin Diabetes Complications Adult Male Middle Aged Disease Progression Blood Glucose Retrospective Studies Electronic Health Records Female Aged
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Development and validation of predictive models for diabetic retinopathy using machine learning.

PloS one Feb 24, 2025
OBJECTIVE: This study aimed to develop and compare machine learning models for predicting diabetic retinopathy (DR) using clinical and biochemical data, specifically logistic regression, random forest, XGBoost, and neural networks.
Area Under Curve Glycated Hemoglobin Adult Male Middle Aged Logistic Models Humans Diabetic Retinopathy Neural Networks, Computer Machine Learning Female Aged
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Optimising test intervals for individuals with type 2 diabetes: A machine learning approach.

PloS one Feb 13, 2025
BACKGROUND: Chronic disease monitoring programs often adopt a one-size-fits-all approach that does not consider variation in need, potentially leading to excessive or insufficient support for patients at different risk levels. Machine learning (ML) d...
Female Aged Adult Male Middle Aged Blood Glucose Diabetes Mellitus, Type 2 Denmark Humans Glycated Hemoglobin Machine Learning Algorithms
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Use of Machine Learning to Predict Individual Postprandial Glycemic Responses to Food Among Individuals With Type 2 Diabetes in India: Protocol for a Prospective Cohort Study.

JMIR research protocols Jan 23, 2025
BACKGROUND: Type 2 diabetes (T2D) is a leading cause of premature morbidity and mortality globally and affects more than 100 million people in the world's most populous country, India. Nutrition is a critical and evidence-based component of effective...
Adult Male Middle Aged Blood Glucose Diabetes Mellitus, Type 2 Humans Machine Learning Prospective Studies Female India Glycated Hemoglobin Postprandial Period
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Predictors of glycaemic improvement in children and young adults with type 1 diabetes and very elevated HbA1c using the MiniMed 780G system.

Diabetes, obesity & metabolism Jan 20, 2025
AIMS: This study aimed to identify key factors with the greatest influence on glycaemic outcomes in young individuals with type 1 diabetes (T1D) and very elevated glycaemia after 3 months of automated insulin delivery (AID).
Diabetes Mellitus, Type 1 Blood Glucose Self-Monitoring Humans Male Hypoglycemic Agents Female Glycemic Control Adolescent Treatment Outcome Young Adult Insulin Infusion Systems Blood Glucose Glycated Hemoglobin Adult Insulin Child
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Perspective: Multiomics and Artificial Intelligence for Personalized Nutritional Management of Diabetes in Patients Undergoing Peritoneal Dialysis.

Advances in nutrition (Bethesda, Md.) Jan 20, 2025
Managing diabetes in patients on peritoneal dialysis (PD) is challenging due to the combined effects of dietary glucose, glucose from dialysate, and other medical complications. Advances in technology that enable continuous biological data collection...
Artificial Intelligence Biomarkers Precision Medicine Blood Glucose Multiomics Humans Peritoneal Dialysis Diabetes Mellitus Metabolomics Glycated Hemoglobin Glycation End Products, Advanced
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Machine learning techniques to predict diabetic ketoacidosis and HbA1c above 7% among individuals with type 1 diabetes - A large multi-centre study in Australia and New Zealand.

Nutrition, metabolism, and cardiovascular diseases : NMCD Jan 9, 2025
BACKGROUND AND AIMS: Type 1 diabetes and diabetic ketoacidosis (DKA) have a significant impact on individuals and society across a wide spectrum. Our objective was to utilize machine learning techniques to predict DKA and HbA1c>7 %.
Risk Factors Young Adult Adult Male Middle Aged Prospective Studies Biomarkers Humans Prognosis Machine Learning Female Decision Support Techniques Support Vector Machine Australia Predictive Value of Tests Glycated Hemoglobin Risk Assessment New Zealand Deep Learning Adolescent Diabetes Mellitus, Type 1 Diabetic Ketoacidosis
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Standardized evaluation of diabetic retinopathy using artificial intelligence and its association with metabolic dysfunction-associated steatotic liver disease in Japan: A cross-sectional study.

PloS one Dec 17, 2024
Metabolic dysfunction-associated steatotic liver disease (MASLD) is common in patients with obesity and diabetes and can lead to serious complications. This study aimed to evaluate fundus photographs using artificial intelligence to explore the relat...
Sensitivity and Specificity Cross-Sectional Studies Male Middle Aged Severity of Illness Index Artificial Intelligence Software Female Risk Factors Humans Japan Liver Cirrhosis Diabetic Retinopathy Image Interpretation, Computer-Assisted Glycated Hemoglobin Photography Fundus Oculi Protective Factors Non-alcoholic Fatty Liver Disease Cholinesterases
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Blood Biomarker Signatures for Slow Gait Speed in Older Adults: An Explainable Machine Learning Approach.

Brain, behavior, and immunity Dec 12, 2024
Maintaining physical function is crucial for independent living in older adults, with gait speed being a key predictor of health outcomes. Blood biomarkers may potentially monitor older adults' mobility, yet their association with slow gait speed sti...
Aging Middle Aged C-Reactive Protein Interleukin-8 Glycated Hemoglobin Gait Humans Walking Speed Female Machine Learning Aged Interleukin-6 Aged, 80 and over Biomarkers Cross-Sectional Studies Male
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