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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)
Last data update: May 16, 2024
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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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Cholesterol-modified prognostic nutritional index (CPNI) as an effective tool for assessing the nutrition status and predicting survival in patients with breast cancer.
Jinyu Shi et al. BMC Med 2023 21(1) 512
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Machine learning model to estimate probability of remission in patients with idiopathic membranous nephropathy.
Lijin Duo et al. Int Immunopharmacol 2023 125(Pt A) 111126
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Machine learning-based prediction model and visual interpretation for prostate cancer.
Gang Chen et al. BMC Urol 2023 23(1) 164
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Development and Multinational Validation of a Novel Algorithmic Strategy for High Lp(a) Screening.
Arya Aminorroaya et al. medRxiv 2023
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Combinatorial Use of Machine Learning and Logistic Regression for Predicting Carotid Plaque Risk Among 5.4 Million Adults With Fatty Liver Disease Receiving Health Check-Ups: Population-Based Cross-Sectional Study.
Yuhan Deng et al. JMIR Public Health Surveill 2023 9e47095
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Machine Learning Applied to Cholesterol-Lowering Pharmacotherapy: Proof-of-Concept in High-Risk Patients Treated in Primary Care.
Andrew J Krentz et al. Metab Syndr Relat Disord 2023
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Machine learning models in predicting health care costs in patients with a recent acute coronary syndrome: A prospective pilot study.
Arto J Hautala et al. Cardiovasc Digit Health J 2023 4(4) 137-142
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Development and validation of explainable machine-learning models for carotid atherosclerosis early screening.
Ke Yun et al. J Transl Med 2023 21(1) 353
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Machine learning for the prediction of cognitive impairment in older adults.
Wanyue Li et al. Front Neurosci 2023 171158141
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Development and Validation of a Prediction Model for Future Estimated Glomerular Filtration Rate in People With Type 2 Diabetes and Chronic Kidney Disease.
Mariella Gregorich et al. JAMA network open 2023 6(4) e231870
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Development and validation of machine learning models for nonalcoholic fatty liver disease.
Hong-Ye Peng et al. Hepatobiliary & pancreatic diseases international : HBPD INT 2023
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Prediction of cardiovascular disease risk based on major contributing features.
Mengxiao Peng et al. Scientific reports 2023 13(1) 4778
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Prediction of the sarcopenia in peritoneal dialysis using simple clinical information: A machine learning-based model.
Jiaying Wu et al. Seminars in dialysis 2023
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Artificial intelligence and body composition.
Prasanna Santhanam et al. Diabetes & metabolic syndrome 2023 17(3) 102732
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Using Machine Learning to Predict Cognitive Impairment Among Middle-Aged and Older Chinese: A Longitudinal Study.
Haihong Liu et al. International journal of public health 2023 681605322
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Development and validation of ischemic heart disease and stroke prognostic models using large-scale real-world data from Japan.
Shigeto Yoshida et al. Environmental health and preventive medicine 2023 2816
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Performance of cardiovascular disease risk prediction equations in more than 14 000 survivors of cancer in New Zealand primary care: a validation study.
Essa Tawfiq et al. Lancet (London, England) 2023
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Risk factors based vessel-specific prediction for stages of coronary artery disease using Bayesian quantile regression machine learning method: Results from the PARADIGM registry.
Hyung-Bok Park et al. Clinical cardiology 2023
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Phenotypes of non-alcoholic fatty liver disease (NAFLD) and all-cause mortality: unsupervised machine learning analysis of NHANES III.
Carrillo-Larco Rodrigo M et al. BMJ open 2022 12(11) e067203
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Predicting diabetic nephropathy in type 2 diabetic patients using machine learning algorithms.
Hosseini Sarkhosh Seyyed Mahdi et al. Journal of diabetes and metabolic disorders 2022 21(2) 1433-1441
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Medication Adherence and Cardiometabolic Control Indicators Among American Indian Adults Receiving Tribal Health Services: Protocol for a Longitudinal Electronic Health Records Study.
Scarton Lisa et al. JMIR research protocols 2022 11(10) e39193
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Evaluating the risk of hypertension in residents in primary care in Shanghai, China with machine learning algorithms.
Chen Ning et al. Frontiers in public health 2022 10984621
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Artificial intelligence-enabled retinal vasculometry for prediction of circulatory mortality, myocardial infarction and stroke.
Rudnicka Alicja Regina et al. The British journal of ophthalmology 2022
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Nomogram-Based Chronic Kidney Disease Prediction Model for Type 1 Diabetes Mellitus Patients Using Routine Pathological Data.
Chowdhury Nakib Hayat et al. Journal of personalized medicine 2022 12(9)
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Analysis of clinical predictors of kidney diseases in type 2 diabetes patients based on machine learning.
Hui Dongna et al. International urology and nephrology 2022
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Integrating Health Data-Driven Machine Learning Algorithms to Evaluate Risk Factors of Early Stage Hypertension at Different Levels of HDL and LDL Cholesterol.
Liao Pen-Chih et al. Diagnostics (Basel, Switzerland) 2022 12(8)
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Using Big Data for Cardiovascular Health Surveillance: Insights From 10.3 Million Individuals in the CANHEART Cohort.
Chu Anna et al. The Canadian journal of cardiology 2022
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Machine learning models of clinically relevant biomarkers for the prediction of stable obstructive coronary artery disease.
Kim Juntae et al. Frontiers in cardiovascular medicine 2022 9933803
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Page last reviewed:
Feb 1, 2024
Page last updated:
May 16, 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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