Transforming Cardiovascular Care With Artificial Intelligence: From Discovery to Practice: JACC State-of-the-Art Review
Artificial intelligence (AI) has the potential to transform every facet of cardiovascular practice
and research. The exponential rise in technology powered by AI is defining new frontiers in …
and research. The exponential rise in technology powered by AI is defining new frontiers in …
Artificial Intelligence Interpretation of the Electrocardiogram: A State-of-the-Art Review
B Ose, Z Sattar, A Gupta, C Toquica, C Harvey… - Current Cardiology …, 2024 - Springer
Many AI models in the domain of cardiac monitors and smart watches have received Food
and Drug Administration (FDA) clearance for rhythm classification, while others for …
and Drug Administration (FDA) clearance for rhythm classification, while others for …
A Multicenter Evaluation of the Impact of Procedural and Pharmacological Interventions on Deep Learning-based Electrocardiographic Markers of Hypertrophic …
Artificial intelligence–enhanced electrocardiography (AI–ECG) interpretation can identify
hypertrophic cardiomyopathy (HCM) on 12–lead ECGs and is a novel way to monitor …
hypertrophic cardiomyopathy (HCM) on 12–lead ECGs and is a novel way to monitor …
[HTML][HTML] Scalable Risk Stratification for Heart Failure Using Artificial Intelligence applied to 12-lead Electrocardiographic Images: A Multinational Study
Background: Current risk stratification strategies for heart failure (HF) risk require either
specific blood-based biomarkers or comprehensive clinical evaluation. In this study, we …
specific blood-based biomarkers or comprehensive clinical evaluation. In this study, we …
Artificial intelligence-enhanced patient evaluation: bridging art and science
EK Oikonomou, R Khera - European Heart Journal, 2024 - academic.oup.com
The advent of digital health and artificial intelligence (AI) has promised to revolutionize
clinical care, but real-world patient evaluation has yet to witness transformative changes. As …
clinical care, but real-world patient evaluation has yet to witness transformative changes. As …
Using Artificial Intelligence to Predict Heart Failure Risk from Single-lead Electrocardiographic Signals: A Multinational Assessment
Importance: Despite the availability of disease-modifying therapies, scalable strategies for
heart failure (HF) risk stratification remain elusive. Portable devices capable of recording …
heart failure (HF) risk stratification remain elusive. Portable devices capable of recording …
Deep Learning Phenotyping of Tricuspid Regurgitation for Automated High Throughput Assessment of Transthoracic Echocardiography
A Vrudhula, M Vukadinovic, C Haeffle, AC Kwan… - medRxiv, 2024 - medrxiv.org
Abstract Background and Aims Diagnosis of tricuspid regurgitation (TR) requires careful
expert evaluation. This study developed an automated deep learning pipeline for assessing …
expert evaluation. This study developed an automated deep learning pipeline for assessing …
[HTML][HTML] A Multicenter Evaluation of the Impact of Therapies on Deep Learning-based Electrocardiographic Hypertrophic Cardiomyopathy Markers
Background Artificial intelligence-enhanced electrocardiography (AI-ECG) can identify
hypertrophic cardiomyopathy (HCM) on 12-lead ECGs and offers a novel way to monitor …
hypertrophic cardiomyopathy (HCM) on 12-lead ECGs and offers a novel way to monitor …