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Public Health Genomics and Precision Health Knowledge Base (v9.0)
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Precision Health Database|Search|Public Health Genomics and Precision Health Knowledge Base (PHGKB)
Diabetes
Last data update: Apr 25, 2024
. (Total: 63675 Documents since 2012)
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all[original query]>>Original Studies[Product Type]
Modification of coronary artery disease clinical risk factors by coronary artery disease polygenic risk score.
Buu Truong et al. Med 2024
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Scalable Approach to Consumer Wearable Postmarket Surveillance: Development and Validation Study.
Richard M Yoo et al. JMIR Med Inform 2024 12e51171
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Predictive analytics support for complex chronic medical conditions: An experience-based co-design study of physician managers' needs and preferences.
Muhammad Rafiq et al. Int J Med Inform 2024 187105447
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Development and validation of machine learning-based models for predicting healthcare-associated bacterial/fungal infections among COVID-19 inpatients: a retrospective cohort study.
Min Wang et al. Antimicrob Resist Infect Control 2024 13(1) 42
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Progression from Prediabetes to Diabetes in a Diverse US Population: a Machine Learning Model.
Joseph Aoki et al. Diabetes Technol Ther 2024
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Development and validation of a machine learning model for prediction of type 2 diabetes in patients with mental illness.
Martin Bernstorff et al. Acta Psychiatr Scand 2024
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Familial aggregation and heritability of childhood-onset and adult-onset type 1 diabetes: a Swedish register-based cohort study.
Yuxia Wei et al. Lancet Diabetes Endocrinol 2024
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Burden of Mendelian disorders in a large Middle Eastern biobank.
Waleed Aamer et al. Genome Med 2024 16(1) 46
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Machine learning to identify a composite indicator to predict cardiac death in ischemic heart disease.
Alessandro Pingitore et al. Int J Cardiol 2024 131981
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Predictive value of ultrasonic artificial intelligence in placental characteristics of early pregnancy for gestational diabetes mellitus.
Huien Zhou et al. Front Endocrinol (Lausanne) 2024 151344666
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PRERISK: A Personalized, Artificial Intelligence-Based and Statistically-Based Stroke Recurrence Predictor for Recurrent Stroke.
Giorgio Colangelo et al. Stroke 2024
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Development and External Validation of Machine Learning Models for Diabetic Microvascular Complications: Cross-Sectional Study With Metabolites.
Feng He et al. J Med Internet Res 2024 26e41065
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Explainable machine learning for early predicting treatment failure risk among patients with TB-diabetes comorbidity.
An-Zhou Peng et al. Sci Rep 2024 14(1) 6814
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A New Tool to Identify Pediatric Patients with Atypical Diabetes Associated with Gene Polymorphisms.
Sophie Welsch et al. Diabetes Metab J 2024
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Family Recall of and Response to Germline Pathologic Variants Found on Paired Tumor-Germline Sequencing in Pediatric Oncology.
Michelle F Jacobs et al. JCO Precis Oncol 2024 8e2300539
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Predictive model and risk analysis for peripheral vascular disease in type 2 diabetes mellitus patients using machine learning and shapley additive explanation.
Lianhua Liu et al. Front Endocrinol (Lausanne) 2024 151320335
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Using machine learning techniques to predict the risk of osteoporosis based on nationwide chronic disease data.
Jun-Bo Tu et al. Sci Rep 2024 14(1) 5245
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Analyzing prehospital delays in recurrent acute ischemic stroke: Insights from interpretable machine learning.
Youli Jiang et al. Patient Educ Couns 2024 123108228
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Enhancing gestational diabetes mellitus risk assessment and treatment through GDMPredictor: a machine learning approach.
J Xing et al. J Endocrinol Invest 2024
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Multi-ancestry polygenic mechanisms of type 2 diabetes
K Smith et al, Nature Medicine, March 6, 2024
Prediction models for earlier stages of chronic kidney disease.
Mackenzie Alexiuk et al. Curr Opin Nephrol Hypertens 2024
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Cloud-Based Machine Learning Platform to Predict Clinical Outcomes at Home for Patients With Cardiovascular Conditions Discharged From Hospital: Clinical Trial.
Phillip C Yang et al. JMIR Cardio 2024 8e45130
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Machine learning based predictive model of Type 2 diabetes complications using Malaysian National Diabetes Registry: A study protocol.
Mohamad Zulfikrie Abas et al. J Public Health Res 2024 13(1) 22799036241231786
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Patients Perceptions of Artificial Intelligence in a Deep Learning-Assisted Diabetic Retinopathy Screening Event: A Real-World Assessment.
Fernando Korn Malerbi et al. J Diabetes Sci Technol 2024 19322968241234378
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Assisting the implementation of screening for type 1 diabetes by using artificial intelligence on publicly available data.
Pedro F Teixeira et al. Diabetologia 2024
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Prediction of Diabetes Using Data Mining and Machine Learning Algorithms: A Cross-Sectional Study.
Hassan Shojaee-Mend et al. Healthc Inform Res 2024 30(1) 73-82
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Automated Machine Learning for Predicting Diabetic Retinopathy Progression From Ultra-Widefield Retinal Images.
Paolo S Silva et al. JAMA Ophthalmol 2024
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Identifying Diabetes Related-Complications in a Real-World Free-Text Electronic Medical Records in Hebrew Using Natural Language Processing Techniques.
Mor Saban et al. J Diabetes Sci Technol 2024 19322968241228555
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Some patients with type 2 diabetes may benefit from intensive glycaemic and blood pressure control: A post-hoc machine learning analysis of ACCORD trial data.
Tianze Jiao et al. Diabetes Obes Metab 2024
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Improving diabetes disease patients classification using stacking ensemble method with PIMA and local healthcare data.
Md Shamim Reza et al. Heliyon 2024 10(2) e24536
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Page last reviewed:
Feb 1, 2024
Page last updated:
Apr 25, 2024
Content source:
Public Health Genomics Branch in the Division of Blood Disorders and Public Health Genomics
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National Center on Birth Defects and Developmental Disabilities
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