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Genomics & Health Impact Scan Database|Search|PHGKB

Last data update: Jan 31, 2023. (Total: 52373 Documents since 2012)
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Query Trace: all[original query]>>Heart, Lung, Blood and Sleep Diseases[Category]
Machine learning in the coagulation and hemostasis arena: an overview and evaluation of methods, review of literature, and future directions.
Hooman H Rashidi et al. Journal of thrombosis and haemostasis : JTH 2023
Multivariate longitudinal data for survival analysis of cardiovascular event prediction in young adults: insights from a comparative explainable study.
Hieu T Nguyen et al. BMC medical research methodology 2023 23(1) 23
Machine learning improves mortality prediction in three-vessel disease.
Xinxing Feng et al. Atherosclerosis 2023 3671-7
Rupture discrimination of multiple small (< 7 mm) intracranial aneurysms based on machine learning-based cluster analysis.
Xin Tong et al. BMC neurology 2023 23(1) 45
Clinical application of multigene panel testing for bleeding, thrombotic, and platelet disorders: a 3-year Belgian experience.
Christine Van Laer et al. Journal of thrombosis and haemostasis : JTH 2023
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
Inflammatory status in pediatric sickle cell disease: Unravelling the role of immune cell subsets.
Silvio Marchesani et al. Frontiers in molecular biosciences 2023 91075686
Sickle Cell Anaemia among Tharu Population Visiting the Outpatient Department of General Medicine in a Secondary Care Centre: A Descriptive Cross-sectional Study.
Subhash Pandey et al. JNMA; journal of the Nepal Medical Association 2023 60(253) 774-776
Proactive Variant Effect Mapping Aids Diagnosis in Pediatric Cardiac Arrest.
Brendan J Floyd et al. Circulation. Genomic and precision medicine 2023
Family History of Sudden Cardiac Death in the Young and Inherited Arrhythmia Syndromes: Awareness and Attitudes of General Practitioners and Private Practice Cardiologists.
Flavia Piciacchia et al. Circulation. Genomic and precision medicine 2023
Collinearity and Dimensionality Reduction in Radiomics: Effect of Preprocessing Parameters in Hypertrophic Cardiomyopathy Magnetic Resonance T1 and T2 Mapping.
Chiara Marzi et al. Bioengineering (Basel, Switzerland) 2023 10(1)
Fully Automatic Left Ventricle Segmentation Using Bilateral Lightweight Deep Neural Network.
Muhammad Ali Shoaib et al. Life (Basel, Switzerland) 2023 13(1)
Machine learning-based approach reveals essential features for simplified TSPO PET quantification in ischemic stroke patients.
Artem Zatcepin et al. Zeitschrift fur medizinische Physik 2023
Validation of a deep-learning-based retinal biomarker (Reti-CVD) in the prediction of cardiovascular disease: data from UK Biobank.
Rachel Marjorie Wei Wen Tseng et al. BMC medicine 2023 21(1) 28
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
Predictive Accuracy of Stroke Risk Prediction Models Across Black and White Race, Sex, and Age Groups.
Chuan Hong et al. JAMA 2023 329(4) 306-317
Prevalence of Diabetes and Its Association with Atherosclerotic Cardiovascular Disease Risk in Patients with Familial Hypercholesterolemia: An Analysis from the Hellenic Familial Hypercholesterolemia Registry (HELLAS-FH).
Boutari Chrysoula et al. Pharmaceuticals (Basel, Switzerland) 2023 16(1)
Combining European and U.S. risk prediction models with polygenic risk scores to refine cardiovascular prevention: the CoLaus|PsyCoLaus Study.
de La Harpe Roxane et al. European journal of preventive cardiology 2023
How to translate and implement the current science of gene therapy into haemophilia care?
Hermans Cedric et al. Therapeutic advances in hematology 2023 1420406207221145627
How does cholesterol burden change the case for investing in familial hypercholesterolaemia? A cost-effectiveness analysis.
Faria Rita et al. Atherosclerosis 2023
Burden of cardiovascular disease in a large contemporary cohort of patients with heterozygous familial hypercholesterolemia.
Ferrières Jean et al. Atherosclerosis plus 2023 5017-24
Polygenic risk score for hypercholesterolemia in a Brazilian familial hypercholesterolemia cohort.
Lima Isabella Ramos et al. Atherosclerosis plus 2023 4947-55
Role of an automated screening tool for familial hypercholesterolemia in patients with premature coronary artery disease.
Jokiniitty Antti et al. Atherosclerosis plus 2023 481-7
Diagnosis of Familial Dysbetalipoproteinemia Based on the Lipid Abnormalities Driven by APOE2/E2 Genotype.
Bea Ana M et al. Clinical chemistry 2023
Cardiovascular disease onset in old people with severe hypercholesterolemia.
Coutinho Elaine R et al. Atherosclerosis 2023 3659-14
Efanesoctocog alfa for hemophilia A: results from a phase 1 repeat-dose study.
Toshko Lissitchkov et al. Blood advances 2021 6(4) 1089-1094
Stroke prevention in rural residents: development of a simplified risk assessment tool with artificial intelligence.
Ding Zhongao et al. Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology 2023
Identification of Coronary Culprit Lesion in ST Elevation Myocardial Infarction by Using Deep Learning.
Tseng Li-Ming et al. IEEE journal of translational engineering in health and medicine 2023 1170-79
Utilization of Personalized Machine-Learning to Screen for Dysglycemia from Ambulatory ECG, toward Noninvasive Blood Glucose Monitoring.
Chiu I-Min et al. Biosensors 2023 13(1)
Imaging and Hemodynamic Characteristics of Vulnerable Carotid Plaques and Artificial Intelligence Applications in Plaque Classification and Segmentation.
Han Na et al. Brain sciences 2023 13(1)
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