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Precision Health Database


Precision Health Database|Search|PHGKB

Heart, Lung, Blood and Sleep Disorders

Last data update: Nov 29, 2023. (Total: 62229 Documents since 2012)
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Records 1 - 18 (of 18 Records)

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A Systematic Review: Do the Use of Machine Learning, Deep Learning, and Artificial Intelligence Improve Patient Outcomes in Acute Myocardial Ischemia Compared to Clinician-Only Approaches?
Binay K Panjiyar et al. Cureus 2023 15(8) e43003
A deep learning-based electrocardiogram risk score for long term cardiovascular death and disease
JW Hughes et al, NPJ Digital Medicine, September 12, 2023
Cardiac Failure Forecasting Based on Clinical Data Using a Lightweight Machine Learning Metamodel.
Istiak Mahmud et al. Diagnostics (Basel) 2023 13(15)
Detection of Cardiovascular Disease from Clinical Parameters Using a One-Dimensional Convolutional Neural Network.
Mohammad Mahbubur Rahman Khan Mamun et al. Bioengineering (Basel) 2023 10(7)
Revolution of echocardiographic reporting: the new era of artificial intelligence and natural language processing.
Kenya Kusunose et al. J Echocardiogr 2023
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
Performance Evaluation of Quantum-Based Machine Learning Algorithms for Cardiac Arrhythmia Classification.
Zeynep Ozpolat et al. Diagnostics (Basel, Switzerland) 2023 13(6)
An intelligent health monitoring and diagnosis system based on the internet of things and fuzzy logic for cardiac arrhythmia COVID-19 patients.
Muhammad Zia Rahman et al. Computers in biology and medicine 2023 154106583
Heart disease detection based on internet of things data using linear quadratic discriminant analysis and a deep graph convolutional neural network.
Saikumar K et al. Frontiers in computational neuroscience 2022 16964686
Medical Professional Enhancement Using Explainable Artificial Intelligence in Fetal Cardiac Ultrasound Screening.
Sakai Akira et al. Biomedicines 2022 10(3)
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
A VLSI Chip for the Abnormal Heart Beat Detection Using Convolutional Neural Network.
Chen Yuan-Ho et al. Sensors (Basel, Switzerland) 2022 22(3)
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
Using Innovative Machine Learning Methods to Screen and Identify Predictors of Congenital Heart Diseases.
Qu Yanji et al. Frontiers in cardiovascular medicine 2022 8797002
Detecting neurodevelopmental trajectories in congenital heart diseases with a machine-learning approach.
Cainelli Elisa et al. Scientific reports 2021 Jan 11(1) 2574
Artificial intelligence and automation in valvular heart diseases.
Long Qiang et al. Cardiology journal 2020 Jun
The Current Research Landscape of the Application of Artificial Intelligence in Managing Cerebrovascular and Heart Diseases: A Bibliometric and Content Analysis.
Tran Bach Xuan et al. International journal of environmental research and public health 2019 Jul 16(15)
Progress Toward Improved Cardiovascular Health in the United States.
Pahigiannis Katherine et al. Circulation 2019 Apr 139(16) 1957-1973
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