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Precision Health Database


Genomics & Health Impact Scan Database|Search|PHGKB

Last data update: Aug 13, 2022. (Total: 48806 Documents since 2012)
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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
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
Precision Phenotyping of Dilated Cardiomyopathy Using Multidimensional Data.
Tayal Upasana et al. Journal of the American College of Cardiology 2022 79(22) 2219-2232
High-Throughput Precision Phenotyping of Left Ventricular Hypertrophy With Cardiovascular Deep Learning.
Duffy Grant et al. JAMA cardiology 2022
Real life experience with the wearable cardioverter-defibrillator in an international multicenter Registry.
El-Battrawy Ibrahim et al. Scientific reports 2022 12(1) 3203
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
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
The role of machine learning in cardiovascular pathology.
Glass Carolyn et al. The Canadian journal of cardiology 2021
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
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
Machine Learning Methods for Identifying Atrial Fibrillation Cases and Their Predictors in Patients With Hypertrophic Cardiomyopathy: The HCM-AF-Risk Model.
Bhattacharya Moumita et al. CJC open 2021 3(6) 801-813
A radiomic approach to predict myocardial fibrosis on coronary CT angiography in hypertrophic cardiomyopathy.
Qin Le et al. International journal of cardiology 2021
Automatic multilabel detection of ICD10 codes in Dutch cardiology discharge letters using neural networks.
Sammani Arjan et al. NPJ digital medicine 2021 4(1) 37
Neural-Network-Based Diagnosis Using 3-Dimensional Myocardial Architecture and Deformation: Demonstration for the Differentiation of Hypertrophic Cardiomyopathy.
Satriano Alessandro et al. Frontiers in cardiovascular medicine 2020 7584727
Deep learning algorithm to improve hypertrophic cardiomyopathy mutation prediction using cardiac cine images.
Zhou Hongyu et al. European radiology 2020 Nov
Machine Learning Outcome Prediction in Dilated Cardiomyopathy Using Regional Left Ventricular Multiparametric Strain.
MacGregor Robert M et al. Annals of biomedical engineering 2020 Oct
Machine learning based classification and diagnosis of clinical cardiomyopathies.
Alimadadi Ahmad et al. Physiological genomics 2020 Aug
Biventricular imaging markers to predict outcomes in non-compaction cardiomyopathy: a machine learning study.
Rocon Camila et al. ESC heart failure 2020 Jun
Development and application of artificial intelligence in cardiac imaging.
Jiang Beibei et al. The British journal of radiology 2020 Feb 20190812
Identifying Ventricular Arrhythmias and Their Predictors by Applying Machine Learning Methods to Electronic Health Records in Patients With Hypertrophic Cardiomyopathy (HCM-VAr-Risk Model).
Bhattacharya Moumita et al. The American journal of cardiology 2019 123(10) 1681-1689
Machine learning detection of obstructive hypertrophic cardiomyopathy using a wearable biosensor
R Ueno et al, NPJ Digital Medicine, December 2019
Three-dimensional Deep Convolutional Neural Networks for Automated Myocardial Scar Quantification in Hypertrophic Cardiomyopathy: A Multicenter Multivendor Study.
Fahmy Ahmed S et al. Radiology 2019 Nov 190737
Machine Learning Prediction of Mortality and Hospitalization in Heart Failure with Preserved Ejection Fraction.
Angraal Suveen et al. JACC. Heart failure 2019 Oct
Machine learning detection of obstructive hypertrophic cardiomyopathy using a wearable biosensor.
Green Eric M, et al. NPJ digital medicine 2019 0 0. 57
UNRAVEL: big data analytics research data platform to improve care of patients with cardiomyopathies using routine electronic health records and standardised biobanking.
Sammani A et al. Netherlands heart journal : monthly journal of the Netherlands Society of Cardiology and the Netherlands Heart Foundation 2019 May
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