AIMC Topic: Prediabetic State
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Development of a 5-Year Risk Prediction Model for Transition From Prediabetes to Diabetes Using Machine Learning: Retrospective Cohort Study.
Journal of medical Internet research
May 9, 2025
BACKGROUND: Diabetes has emerged as a critical global public health crisis. Prediabetes, as the transitional phase with 5%-10% annual progression to diabetes, offers a critical window for intervention. The lack of a 5-year risk prediction model for d...
Development and Validation of Machine Learning Models for Identifying Prediabetes and Diabetes in Normoglycemia.
Diabetes/metabolism research and reviews
Nov 1, 2024
BACKGROUND: Prediabetes and diabetes are both abnormal states of glucose metabolism (AGM) that can lead to severe complications. Early detection of AGM is crucial for timely intervention and treatment. However, fasting blood glucose (FBG) as a mass p...
Exploring Prediabetes Pathways Using Explainable AI on Data from Electronic Medical Records.
Studies in health technology and informatics
Aug 22, 2024
This study leverages data from a Canadian database of primary care Electronic Medical Records to develop machine learning models predicting type 2 diabetes mellitus (T2D), prediabetes, or normoglycemia. These models are used as a basis for extracting...
Identifying Prediabetes in Canadian Populations Using Machine Learning.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
Prediabetes is a critical health condition characterized by elevated blood glucose levels that fall below the threshold for Type 2 diabetes (T2D) diagnosis. Accurate identification of prediabetes is essential to forestall the progression to T2D among...
An interpretable predictive deep learning platform for pediatric metabolic diseases.
Journal of the American Medical Informatics Association : JAMIA
May 20, 2024
OBJECTIVES: Metabolic disease in children is increasing worldwide and predisposes a wide array of chronic comorbid conditions with severe impacts on quality of life. Tools for early detection are needed to promptly intervene to prevent or slow the de...
Exploration of Machine Learning and Statistical Techniques in Development of a Low-Cost Screening Method Featuring the Global Diet Quality Score for Detecting Prediabetes in Rural India.
The Journal of nutrition
Oct 23, 2021
BACKGROUND: The prevalence of type 2 diabetes has increased substantially in India over the past 3 decades. Undiagnosed diabetes presents a public health challenge, especially in rural areas, where access to laboratory testing for diagnosis may not b...
A combined strategy of feature selection and machine learning to identify predictors of prediabetes.
Journal of the American Medical Informatics Association : JAMIA
Mar 1, 2020
OBJECTIVE: To identify predictors of prediabetes using feature selection and machine learning on a nationally representative sample of the US population.
An outcome model approach to transporting a randomized controlled trial results to a target population.
Journal of the American Medical Informatics Association : JAMIA
May 1, 2019
OBJECTIVE: Participants enrolled into randomized controlled trials (RCTs) often do not reflect real-world populations. Previous research in how best to transport RCT results to target populations has focused on weighting RCT data to look like the tar...
Humans
Machine Learning
Electronic Health Records
Cardiovascular Diseases
Disease Progression
Diabetes Mellitus, Type 2
Hypoglycemic Agents
Randomized Controlled Trials as Topic
Antihypertensive Agents
Prediabetic State
Nateglinide
Translational Research, Biomedical
Outcome Assessment, Health Care
Valsartan
Evidence-Based Medicine
Increased lipocalin-2 vs reduced oxytocin in relation with adiposity, atherogenicity and hematological indices in metabolic syndrome patients with and without prediabetes.
Bratislavske lekarske listy
Jan 1, 2018
OBJECTIVES: The neuropeptide hormone- Oxytocin (OXT) and glycoprotein Lipocalin-2 (LCN-2) are strongly associated with cardiometabolic risks of insulin resistance in metabolic syndrome (MetS) and prediabetes (preDM).
The Effect of Vitamin D Supplementation on Metabolic Phenotypes in Thais with Prediabetes.
Journal of the Medical Association of Thailand = Chotmaihet thangphaet
Dec 1, 2015
OBJECTIVE: To investigate the effects of vitamin D supplement for three months on anthropometric and glucose homeostatic measures in Thai adults with impaired fasting glucose (IFG) and/or impaired glucose tolerance (IGT).
Asian People
Tandem Mass Spectrometry
Biological Availability
Humans
Glucose Tolerance Test
Male
Cholecalciferol
Regression Analysis
Phenotype
Anthropometry
Middle Aged
Prediabetic State
Drug Monitoring
Female
Insulin Resistance
Ergocalciferols
Vitamins
Adult
Treatment Outcome
Calcifediol
Dietary Supplements
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