[HTML][HTML] State-of-the-art deep learning methods on electrocardiogram data: systematic review
Background Electrocardiogram (ECG) is one of the most common noninvasive diagnostic
tools that can provide useful information regarding a patient's health status. Deep learning …
tools that can provide useful information regarding a patient's health status. Deep learning …
Clinical applications, methodology, and scientific reporting of electrocardiogram deep-learning models: A systematic review
Background The electrocardiogram (ECG) is one of the most common diagnostic tools
available to assess cardiovascular health. The advent of advanced computational …
available to assess cardiovascular health. The advent of advanced computational …
Electrocardiogram-based heart age estimation by a deep learning model provides more information on the incidence of cardiovascular disorders
CH Chang, CS Lin, YS Luo, YT Lee… - Frontiers in Cardiovascular …, 2022 - frontiersin.org
Objective The biological age progression of the heart varies from person to person. We
developed a deep learning model (DLM) to predict the biological age via ECG to explore its …
developed a deep learning model (DLM) to predict the biological age via ECG to explore its …
Point-of-care artificial intelligence-enabled ECG for dyskalemia: A retrospective cohort analysis for accuracy and outcome prediction
Dyskalemias are common electrolyte disorders associated with high cardiovascular risk.
Artificial intelligence (AI)-assisted electrocardiography (ECG) has been evaluated as an …
Artificial intelligence (AI)-assisted electrocardiography (ECG) has been evaluated as an …
Clinical significance, challenges and limitations in using artificial intelligence for electrocardiography-based diagnosis
Cardiovascular diseases are one of the leading global causes of mortality. Currently,
clinicians rely on their own analyses or automated analyses of the electrocardiogram (ECG) …
clinicians rely on their own analyses or automated analyses of the electrocardiogram (ECG) …
Biomedical big data technologies, applications, and challenges for precision medicine: A review
The explosive growth of biomedical Big Data presents both significant opportunities and
challenges in the realm of knowledge discovery and translational applications within …
challenges in the realm of knowledge discovery and translational applications within …
Artificial intelligence-enabled electrocardiogram estimates left atrium enlargement as a predictor of future cardiovascular disease
YS Lou, CS Lin, WH Fang, CC Lee, CL Ho… - Journal of Personalized …, 2022 - mdpi.com
Background: Left atrium enlargement (LAE) can be used as a predictor of future
cardiovascular diseases, including hypertension (HTN) and atrial fibrillation (Afib). Typical …
cardiovascular diseases, including hypertension (HTN) and atrial fibrillation (Afib). Typical …
Artificial intelligence-enabled electrocardiography predicts left ventricular dysfunction and future cardiovascular outcomes: a retrospective analysis
BACKGROUND: The ejection fraction (EF) provides critical information about heart failure
(HF) and its management. Electrocardiography (ECG) is a noninvasive screening tool for …
(HF) and its management. Electrocardiography (ECG) is a noninvasive screening tool for …
Deep learning algorithm for management of diabetes mellitus via electrocardiogram-based glycated hemoglobin (ECG-HbA1c): a retrospective cohort study
CS Lin, YT Lee, WH Fang, YS Lou, FC Kuo… - Journal of Personalized …, 2021 - mdpi.com
Background: glycated hemoglobin (HbA1c) provides information on diabetes mellitus (DM)
management. Electrocardiography (ECG) is a noninvasive test of cardiac activity that has …
management. Electrocardiography (ECG) is a noninvasive test of cardiac activity that has …
Artificial intelligence-enabled electrocardiogram predicted left ventricle diameter as an independent risk factor of long-term cardiovascular outcome in patients with …
Background Heart failure (HF) is a global disease with increasing prevalence in an aging
society. However, the survival rate is poor despite the patient receiving standard treatment …
society. However, the survival rate is poor despite the patient receiving standard treatment …