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Postprandial Period

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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 35568422
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...
Blood Glucose Diabetes Mellitus, Type 1 Fibrinogen Humans Hypoglycemic Agents Injections, Subcutaneous Insulin Insulin Resistance Insulin, Short-Acting Machine Learning Plasminogen Activator Inhibitor 1 Postprandial Period
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Overweight postmenopausal women with different plasma estradiol concentrations present with a similar pattern of energy expenditure and substrate oxidation rate before and after a fatty meal challenge.

Clinical nutrition ESPEN 28531779
Menopause-related withdrawal of ovarian estrogens is associated with reduced energy metabolism and overall impairment of substrate oxidation. Estradiol's withdrawal after menopause is associated with a reduction in energy metabolism and impaired subs...
Body Composition Body Mass Index Calorimetry, Indirect Carbohydrate Metabolism Child Dietary Fats Eating Energy Metabolism Estradiol Estrogens Female Humans Intra-Abdominal Fat Lipid Metabolism Meals Menopause Middle Aged Obesity Oxidation-Reduction Postmenopause Postprandial Period
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Alpha-Linolenic Acid-Enriched Diacylglycerol Oil Suppresses the Postprandial Serum Triglyceride Level-A Randomized, Double-Blind, Placebo-Controlled, Crossover Study.

Journal of nutritional science and vitaminology 28202845
This study investigated the effect of a single oral ingestion of alpha-linolenic acid-enriched diacylglycerol (ALA-DAG) on postprandial serum triglyceride (TG) levels. A randomized, double-blind, controlled, crossover study was performed in subjects ...
Adult alpha-Linolenic Acid Cross-Over Studies Dietary Fats Diglycerides Dose-Response Relationship, Drug Double-Blind Method Fasting Female Humans Insulin Male Middle Aged Postprandial Period Triglycerides
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Risk-based postprandial hypoglycemia forecasting using supervised learning.

International journal of medical informatics 31029250
BACKGROUND: Predicting insulin-induced postprandial hypoglycemic events is critical for the safety of type 1 diabetes patients because an early warning of hypoglycemia facilitates correction of the insulin bolus before its administration. The postpra...
Blood Glucose Diabetes Mellitus, Type 1 Female Forecasting Humans Hypoglycemia Hypoglycemic Agents Insulin Insulin Infusion Systems Male Postprandial Period Retrospective Studies Supervised Machine Learning
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Minimizing postprandial hypoglycemia in Type 1 diabetes patients using multiple insulin injections and capillary blood glucose self-monitoring with machine learning techniques.

Computer methods and programs in biomedicine 31416546
BACKGROUND: Diabetic patients treated with intensive insulin therapies require a tight glycemic control and may benefit from advanced tools to predict blood glucose (BG) concentration levels and hypo/hyperglycemia events. Prediction systems using mac...
Adult Algorithms Bayes Theorem Blood Glucose Blood Glucose Self-Monitoring Capillaries Computer Simulation Diabetes Mellitus, Type 1 False Positive Reactions Female Humans Hypoglycemia Hypoglycemic Agents Insulin Insulin Infusion Systems Machine Learning Male Middle Aged Normal Distribution Postprandial Period Reproducibility of Results Retrospective Studies Sensitivity and Specificity
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Optimizing postprandial glucose prediction through integration of diet and exercise: Leveraging transfer learning with imbalanced patient data.

PloS one 39088422
BACKGROUND: In recent years, numerous methods have been introduced to predict glucose levels using machine-learning techniques on patients' daily behavioral and continuous glucose data. Nevertheless, a definitive consensus remains elusive regarding m...
Adult Bayes Theorem Blood Glucose Diabetes, Gestational Diet Exercise Female Humans Machine Learning Postprandial Period Pregnancy
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Amount Estimation Method for Food Intake Based on Color and Depth Images through Deep Learning.

Sensors (Basel, Switzerland) 38610258
In this paper, we propose an amount estimation method for food intake based on both color and depth images. Two pairs of color and depth images are captured pre- and post-meals. The pre- and post-meal color images are employed to detect food types an...
Computer Simulation Deep Learning Eating Food Postprandial Period
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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 39847416
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 Blood Glucose Diabetes Mellitus, Type 2 Female Glycated Hemoglobin Humans India Machine Learning Male Middle Aged Postprandial Period Prospective Studies
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