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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)
Heart, Lung, Blood and Sleep Disorders
Last data update: Mar 28, 2024
. (Total: 63390 Documents since 2012)
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Heart And Vascular Diseases[original query]
Development and Validation of Machine Learning Algorithms to Predict 1-Year Ischemic Stroke and Bleeding Events in Patients with Atrial Fibrillation and Cancer.
Bang Truong et al. Cardiovasc Toxicol 2024
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Explainable machine learning using echocardiography to improve risk prediction in patients with chronic coronary syndrome.
Mitchel A Molenaar et al. Eur Heart J Digit Health 2024 5(2) 170-182
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Emerging artificial intelligence-aided diagnosis and management methods for ischemic strokes and vascular occlusions: A comprehensive review.
G A U R I Parvathy et al. World Neurosurg X 2024 22100303
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Interpretable prediction models for disability in older adults with hypertension: the Chinese Longitudinal Healthy Longevity and Happy Family Study.
Yafei Wu et al. Psychogeriatrics 2024
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Artificial intelligence-enabled prediction of chemotherapy-induced cardiotoxicity from baseline electrocardiograms.
Ryuichiro Yagi et al. Nat Commun 2024 15(1) 2536
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Automated valvular heart disease detection using heart sound with a deep learning algorithm.
Zihan Jiang et al. Int J Cardiol Heart Vasc 2024 51101368
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Machine Learning to Predict Outcomes of Endovascular Intervention for Patients With PAD.
Ben Li et al. JAMA Netw Open 2024 7(3) e242350
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An Arrhythmia classification approach via deep learning using single-lead ECG without QRS wave detection.
Liong-Rung Liu et al. Heliyon 2024 10(5) e27200
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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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Using the Super Learner algorithm to predict risk of major adverse cardiovascular events after percutaneous coronary intervention in patients with myocardial infarction.
Xiang Zhu et al. BMC Med Res Methodol 2024 24(1) 59
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Sleep-phasic heart rate variability predicts stress severity: Building a machine learning-based stress prediction model.
Jingjing Fan et al. Stress Health 2024 e3386
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A machine learning-based risk score for prediction of infective endocarditis among patients with Staphylococcus aureus bacteraemia - The SABIER score.
Christopher Koon-Chi Lai et al. J Infect Dis 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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Developmental Prediction of Poststroke Patients in Activities of Daily Living by Using Tree-Structured Parzen Estimator-Optimized Stacking Ensemble Approaches.
Pei-Hua Lin et al. IEEE J Biomed Health Inform 2024 PP
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An ECG-based artificial intelligence model for assessment of sudden cardiac death risk
L Holmstrom et al, Comm Med, February 2024
Convolutional neural networks combined with classification algorithms for the diagnosis of periodontitis.
Fang Dai et al. Oral Radiol 2024
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An ecological examination of early adolescent e-cigarette use: A machine learning approach to understanding a health epidemic.
Alejandro L Vázquez et al. PLoS One 2024 19(2) e0287878
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Electrocardiography deep-learning models to predict high-risk Imaging features in Patients with Hypertrophic Cardiomyopathy: Can It Change Clinical Practice?
Ghassan Bidaoui et al. Heart Rhythm 2024
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Coronary artery disease evaluation during transcatheter aortic valve replacement work-up using photon-counting CT and artificial intelligence.
Jan M Brendel et al. Diagn Interv Imaging 2024
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A Clinical and Imaging Fused Deep Learning Model Matches Expert Clinician Prediction of 90-Day Stroke Outcomes.
Yongkai Liu et al. AJNR Am J Neuroradiol 2024
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Characterizing Advanced Heart Failure Risk and HemodyNAmic Phenotypes using Interpretable Machine Learning.
Josephine Lamp et al. Am Heart J 2024
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Coronary heart disease classification using deep learning approach with feature selection for improved accuracy.
Anandhavalli Muniasamy et al. Technol Health Care 2024
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Large datasets from Electronic Health Records predict seizures after ischemic strokes: A Machine Learning approach.
Alain Lekoubou et al. medRxiv 2024
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Echocardiographic artificial intelligence for pulmonary hypertension classification.
Yukina Hirata et al. Heart 2024
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Predictive modeling for acute kidney injury after percutaneous coronary intervention in patients with acute coronary syndrome: a machine learning approach.
Amir Hossein Behnoush et al. Eur J Med Res 2024 29(1) 76
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Machine learning-based prediction of composite risk of cardiovascular events in patients with stable angina pectoris combined with coronary heart disease: development and validation of a clinical prediction model for Chinese patients.
Zihan Wang et al. Front Pharmacol 2024 141334439
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Digital Health for Myocardial Infarction: Research Topics and Trends.
Melissa Pelly et al. Stud Health Technol Inform 2024 310429-433
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Role of artificial intelligence in early detection of congenital heart diseases in neonates.
Haris Ejaz et al. Front Digit Health 2024 51345814
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Page last reviewed:
Feb 1, 2024
Page last updated:
Mar 28, 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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