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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: Apr 23, 2024
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all[original query]>>Original Studies[Product Type]
Identifying dementia from cognitive footprints in hospital records among Chinese older adults: a machine-learning study.
Jiayi Zhou et al. Lancet Reg Health West Pac 2024 46101060
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Impact of Race, Socioeconomic Status, and Geography on Healthcare Outcomes for Children With Sickle Cell Disease in the United States: A Scoping Review
Family cascade screening for equitable identification of familial hypercholesterolemia: study protocol for a hybrid effectiveness-implementation type III randomized controlled trial
Family cascade screening for equitable identification of familial hypercholesterolemia: study protocol for a hybrid effectiveness-implementation type III randomized controlled trial.
Christina Johnson et al. Implement Sci 2024 19(1) 30
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Prevalence of elevated lipoprotein(a) in cardiac rehabilitation patients - results from a large-scale multicentre registry in Germany.
Christoph Altmann et al. Clin Res Cardiol 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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Non-Invasive Heart Failure Evaluation Using Machine Learning Algorithms.
Odeh Adeyi Victor et al. Sensors (Basel) 2024 24(7)
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Infodemiology of Influenza-like Illness: Utilizing Google Trends' Big Data for Epidemic Surveillance.
Dong-Her Shih et al. J Clin Med 2024 13(7)
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Development of a Non-Invasive Machine-Learned Point-of-Care Rule-Out Test for Coronary Artery Disease.
Timothy Burton et al. Diagnostics (Basel) 2024 14(7)
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Deep learning evaluation of echocardiograms to identify occult atrial fibrillation.
Neal Yuan et al. NPJ Digit Med 2024 7(1) 96
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Awareness of sickle cell disease among nursing undergraduates in Farasan: Its interference with malaria.
Shabihul Fatma Sayed et al. J Family Med Prim Care 2024 13(2) 589-599
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Cardiovascular Risk Factors Among First-Degree Relatives of Patients with Premature Cardiovascular Disease in Malta. Baseline Findings from the CRISO Project.
Justin Lee Mifsud et al. Vasc Health Risk Manag 2024 20167-176
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The outcome of genetic and non-genetic pediatric cardiomyopathies.
Ali AlAlakhfash et al. Egypt Heart J 2024 76(1) 43
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Ethical use of artificial intelligence to prevent sudden cardiac death: an interview study of patient perspectives.
Menno T Maris et al. BMC Med Ethics 2024 25(1) 42
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Newborn Screening for Severe T and B Cell Lymphopenia Using TREC/KREC Detection: A Large-Scale Pilot Study of 202,908 Newborns.
Andrey V Marakhonov et al. J Clin Immunol 2024 44(4) 93
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Artificial intelligence-guided detection of under-recognized cardiomyopathies on point-of-care cardiac ultrasound.
Evangelos K Oikonomou et al. medRxiv 2024
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Automated Extraction of Stroke Severity from Unstructured Electronic Health Records using Natural Language Processing.
Marta Fernandes et al. medRxiv 2024
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Performance of risk models to predict mortality risk for patients with heart failure: evaluation in an integrated health system.
Faraz S Ahmad et al. Clin Res Cardiol 2024
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Comprehensive evaluation and performance analysis of machine learning in heart disease prediction.
Halah A Al-Alshaikh et al. Sci Rep 2024 14(1) 7819
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Machine Learning-Based Prediction of Stroke in Emergency Departments.
Vida Abedi et al. Ther Adv Neurol Disord 2024 1717562864241239108
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Iowa Newborn Screening Program Experience with Hemoglobinopathy Screening over the Last Two Decades and Its Increasing Global Relevance.
Ryan Jilek et al. Int J Neonatal Screen 2024 10(1)
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Current Methods of Newborn Screening Follow-Up for Sickle Cell Disease Are Highly Variable and without Quality Assurance: Results from the ENHANCE Study.
Najibah Galadanci et al. Int J Neonatal Screen 2024 10(1)
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The Health History of First-Degree Relatives' Dyslipidemia Can Affect Preferences and Intentions following the Return of Genomic Results for Monogenic Familial Hypercholesterolemia.
Tomoharu Tokutomi et al. Genes (Basel) 2024 15(3)
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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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Machine learning prediction of refractory ventricular fibrillation in out-of-hospital cardiac arrest using features available to EMS.
Rayhan Erlangga Rahadian et al. Resusc Plus 2024 18100606
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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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Echocardiographic Detection of Regional Wall Motion Abnormalities using Artificial Intelligence Compared to Human Readers.
Jeremy A Slivnick et al. J Am Soc Echocardiogr 2024
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Utilizing ultra-early continuous physiologic data to develop automated measures of clinical severity in a traumatic brain injury population.
Shiming Yang et al. Sci Rep 2024 14(1) 7618
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The Hypotension Prediction Index is equally effective in predicting intraoperative hypotension during non-cardiac surgery compared to a mean arterial pressure threshold: a prospective observational study.
Marijn P Mulder et al. Anesthesiology 2024
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Birth Prevalence of Sickle Cell Disease and County-Level Social Vulnerability - Sickle Cell Data Collection Program, 11 States, 2016-2020.
Mariam Kayle et al. MMWR Morb Mortal Wkly Rep 2024 73(12) 248-254
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Page last reviewed:
Feb 1, 2024
Page last updated:
Apr 23, 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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