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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 18, 2024
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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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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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Identification of Hypertrophic Cardiomyopathy on Electrocardiographic Images with Deep Learning.
Veer Sangha et al. medRxiv 2024
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Echocardiography-Based Deep Learning Model to Differentiate Constrictive Pericarditis and Restrictive Cardiomyopathy.
Chieh-Ju Chao et al. JACC Cardiovasc Imaging 2023
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Detecting transthyretin amyloid cardiomyopathy (ATTR-CM) using machine learning: an evaluation of the performance of an algorithm in a UK setting.
Carmen Tsang et al. BMJ Open 2023 13(10) e070028
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Association Between Wearable Device Measured Activity and Patient-Reported Outcomes for Heart Failure.
Jessica R Golbus et al. JACC Heart Fail 2023
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Artificial intelligence in cardiovascular diseases: diagnostic and therapeutic perspectives.
Xiaoyu Sun et al. Eur J Med Res 2023 28(1) 242
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Preterm birth and maternal heart disease: A machine learning analysis using the Korean national health insurance database.
Jue Seong Lee et al. PloS one 2023 18(3) e0283959
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Performance Evaluation of Quantum-Based Machine Learning Algorithms for Cardiac Arrhythmia Classification.
Zeynep Ozpolat et al. Diagnostics (Basel, Switzerland) 2023 13(6)
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A second-generation artificial intelligence-based therapeutic regimen improves diuretic resistance in heart failure: Results of a feasibility open-labeled clinical trial.
Ram Gelman et al. Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie 2023 161114334
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Development and validation of echocardiography-based machine-learning models to predict mortality.
Akshay Valsaraj et al. EBioMedicine 2023 90104479
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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)
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Tandem deep learning and logistic regression models to optimize hypertrophic cardiomyopathy detection in routine clinical practice.
Maanja Maren et al. Cardiovascular digital health journal 2023 3(6) 289-296
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Machine learning approach in diagnosing Takotsubo cardiomyopathy: The role of the combined evaluation of atrial and ventricular strain, and parametric mapping.
Cau Riccardo et al. International journal of cardiology 2022
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Identification of fibrosis in hypertrophic cardiomyopathy: a radiomic study on cardiac magnetic resonance cine imaging.
Pu Cailing et al. European radiology 2022
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Predictors of Adherence to Stroke Prevention in the BALKAN-AF Study: A Machine-Learning Approach.
Koziel-Siolkowska Monika et al. TH open : companion journal to thrombosis and haemostasis 2022 6(3) e283-e290
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From evidence-based medicine to digital twin technology for predicting ventricular tachycardia in ischaemic cardiomyopathy.
de Lepper Anouk G W et al. Journal of the Royal Society, Interface 2022 19(194) 20220317
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Artificial Intelligence Applied to Cardiomyopathies: Is It Time for Clinical Application?
Kim Kyung-Hee et al. Current cardiology reports 2022
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Machine learning to predict left ventricular reverse remodeling by guideline-directed medical therapy by utilizing texture feature of extracellular volume fraction in patients with non-ischemic dilated cardiomyopathy.
Suyama Shun et al. Heart and vessels 2022
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Passively Captured Interpersonal Social Interactions and Motion From Smartphones for Predicting Decompensation in Heart Failure: Observational Cohort Study.
Cakmak Ayse S et al. JMIR formative research 2022 6(8) e36972
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Machine Learning Patient-Specific Prediction of Heart Failure Hospitalization Using Cardiac MRI-Based Phenotype and Electronic Health Information.
Cornhill Aidan K et al. Frontiers in cardiovascular medicine 2022 9890904
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Radiomics and deep learning for myocardial scar screening in hypertrophic cardiomyopathy.
Fahmy Ahmed S et al. Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance 2022 24(1) 40
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Precision Phenotyping of Dilated Cardiomyopathy Using Multidimensional Data.
Tayal Upasana et al. Journal of the American College of Cardiology 2022 79(22) 2219-2232
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High-Throughput Precision Phenotyping of Left Ventricular Hypertrophy With Cardiovascular Deep Learning.
Duffy Grant et al. JAMA cardiology 2022
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Real life experience with the wearable cardioverter-defibrillator in an international multicenter Registry.
El-Battrawy Ibrahim et al. Scientific reports 2022 12(1) 3203
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Artificial intelligence study on left ventricular function among normal individuals, hypertrophic cardiomyopathy and dilated cardiomyopathy patients using 1.5T cardiac cine MR images obtained by SSFP sequence.
Guo Jiajun et al. The British journal of radiology 2022 20201060
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Detecting cardiomyopathies in pregnancy and the postpartum period with an electrocardiogram-based deep learning model.
Adedinsewo Demilade A et al. European heart journal. Digital health 2022 2(4) 586-596
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The role of machine learning in cardiovascular pathology.
Glass Carolyn et al. The Canadian journal of cardiology 2021
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Explanatory Analysis of a Machine Learning Model to Identify Hypertrophic Cardiomyopathy Patients from EHR Using Diagnostic Codes.
Farahani Nasibeh Zanjirani et al. Proceedings. IEEE International Conference on Bioinformatics and Biomedicine 2021 20201932-1937
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A machine learning-based risk stratification model for ventricular tachycardia and heart failure in hypertrophic cardiomyopathy.
Smole Tim et al. Computers in biology and medicine 2021 135104648
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Page last reviewed:
Feb 1, 2024
Page last updated:
Apr 18, 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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