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Precision Health Database


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Heart, Lung, Blood and Sleep Disorders

Last data update: Jun 01, 2023. (Total: 60046 Documents since 2012)
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Query Trace: Coronary Heart Disease[original query]>>Original Studies[Product Type]
Coronary Artery Calcium Score and Polygenic Risk Score for the Prediction of Coronary Heart Disease Events
SS Khan et al, JAMA Network Open, May 23, 2023
Familial Hypercholesterolemia in the Electronic Medical Records and Genomics Network: Prevalence, Penetrance, Cardiovascular Risk, and Outcomes After Return of Results.
Ozan Dikilitas et al. Circ Genom Precis Med 2023 16(2) e003816
Performance Evaluation of Quantum-Based Machine Learning Algorithms for Cardiac Arrhythmia Classification.
Zeynep Ozpolat et al. Diagnostics (Basel, Switzerland) 2023 13(6)
Familial Associations of Complete Atrioventricular Block: A National Family Study in Sweden.
Artur Fedorowski et al. Circulation. Genomic and precision medicine 2023 e003654
Validation of risk prediction models applied to longitudinal electronic health record data for the prediction of major cardiovascular events in the presence of data shifts.
Yikuan Li et al. European heart journal. Digital health 2023 3(4) 535-547
Association of Rare Protein-Truncating DNA Variants in APOB or PCSK9 With Low-density Lipoprotein Cholesterol Level and Risk of Coronary Heart Disease.
Jacqueline S Dron et al. JAMA cardiology 2023
Cardiovascular risk-enhancing factors and coronary artery calcium in South Asian American adults: The MASALA study.
Shah Harini et al. American journal of preventive cardiology 2023 13100453
Predictive value of CAC score combined with clinical features for obstructive coronary heart disease on coronary computed tomography angiography: a machine learning method.
Ren Yongkui et al. BMC cardiovascular disorders 2022 22(1) 569
Development and evaluation of a radiomics model of resting N-ammonia positron emission tomography myocardial perfusion imaging to predict coronary artery stenosis in patients with suspected coronary heart disease.
Zhang Xiaochun et al. Annals of translational medicine 2022 10(21) 1167
Discovery and systematic characterization of risk variants and genes for coronary artery disease in over a million participants
KG Aragam et al, Nature Genetics, December 6, 2022
Recurrence risk prediction of acute coronary syndrome per patient as a personalized ACS recurrence risk: a retrospective study.
Kong Vungsovanreach et al. PeerJ 2022 10e14348
A clinical decision support system for predicting coronary artery stenosis in patients with suspected coronary heart disease.
Yan Jingjing et al. Computers in biology and medicine 2022 151(Pt A) 106300
Study on the risk of coronary heart disease in middle-aged and young people based on machine learning methods: a retrospective cohort study.
Cao Jiaoyu et al. PeerJ 2022 10e14078
A Machine Learning Model to Predict Cardiovascular Events during Exercise Evaluation in Patients with Coronary Heart Disease.
Shen Tao et al. Journal of clinical medicine 2022 11(20)
The burden of severe hypercholesterolemia and familial hypercholesterolemia in a population-based setting in the US.
Saadatagah Seyedmohammad et al. American journal of preventive cardiology 2022 12100393
Predictive Utility of a Validated Polygenic Risk Score for Long-Term Risk of Coronary Heart Disease in Young and Middle-Aged Adults.
Khan Sadiya S et al. Circulation 2022 101161CIRCULATIONAHA121058426
Development and Validation of Prediction Models of Adverse Kidney Outcomes in the Population With and Without Diabetes Mellitus.
Grams Morgan E et al. Diabetes care 2022
Risk Assessment of CHD Using Retinal Images with Machine Learning Approaches for People with Cardiometabolic Disorders.
Qu Yimin et al. Journal of clinical medicine 2022 11(10)
Risk Prediction of Major Adverse Cardiovascular Events Occurrence Within 6 Months After Coronary Revascularization: Machine Learning Study.
Wang Jinwan et al. JMIR medical informatics 2022 10(4) e33395
[Sudden cardiac death in young people and in adults: primary and contributing causes. The experience of the multidisciplinary network in Emilia-Romagna].
Leone Ornella et al. Giornale italiano di cardiologia (2006) 2022 23(3) 200-210
Nonlaboratory-based risk assessment model for coronary heart disease screening: Model development and validation.
Zhang Liying et al. International journal of medical informatics 2022 162104746
Common genetic variants do not predict recurrent events in coronary heart disease patients.
Thompson P L et al. BMC cardiovascular disorders 2022 22(1) 96
Integration of questionnaire-based risk factors improves polygenic risk scores for human coronary heart disease and type 2 diabetes.
Tamlander Max et al. Communications biology 2022 5(1) 158
Learning dynamic treatment strategies for coronary heart diseases by artificial intelligence: real-world data-driven study.
Guo Haihong et al. BMC medical informatics and decision making 2022 22(1) 39
Deep Phenotyping and Prediction of Long-Term Cardiovascular Disease: Optimized by Machine Learning.
Zhuang Xiao-Dong et al. The Canadian journal of cardiology 2022
Predicting Coupled Herbs for the Treatment of Hypertension Complicated with Coronary Heart Disease in Real-World Data Based on a Complex Network and Machine Learning.
Huan Jia-Ming et al. Evidence-based complementary and alternative medicine : eCAM 2022 20228285111
The Pharmacogenetics of Statin Therapy on Clinical Events: No Evidence that Genetic Variation Affects Statin Response on Myocardial Infarction.
Trompet Stella et al. Frontiers in pharmacology 2022 12679857
Identifying Coronary Artery Lesions by Feature Analysis of Radial Pulse Wave: A Case-Control Study.
Zhang Chun-Ke et al. BioMed research international 2022 20215047501
ECG-AI: electrocardiographic artificial intelligence model for prediction of heart failure.
Akbilgic Oguz et al. European heart journal. Digital health 2022 2(4) 626-634
Prognostic Value of a Polygenic Risk Score for Coronary Heart Disease in Individuals Aged 70 Years and Older.
Neumann Johannes T et al. Circulation. Genomic and precision medicine 2021 CIRCGEN121003429
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