Artificial neural networks for ECG interpretation in acute coronary syndrome: A sco** review

AJ Bishop, Z Nehme, S Nanayakkara… - The American Journal of …, 2024 - Elsevier
Introduction The electrocardiogram (ECG) is a crucial diagnostic tool in the Emergency
Department (ED) for assessing patients with Acute Coronary Syndrome (ACS). Despite its …

[HTML][HTML] AI-Enhanced ECG Applications in Cardiology: Comprehensive Insights from the Current Literature with a Focus on COVID-19 and Multiple Cardiovascular …

LC Nechita, A Nechita, AE Voipan, D Voipan, M Debita… - Diagnostics, 2024 - mdpi.com
The application of artificial intelligence (AI) in electrocardiography is revolutionizing
cardiology and providing essential insights into the consequences of the COVID-19 …

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 …

Artificial intelligence–powered rapid identification of ST-elevation myocardial infarction via electrocardiogram (ARISE)—a pragmatic randomized controlled trial

C Lin, WT Liu, CH Chang, CC Lee, SC Hsing, WH Fang… - NEJM AI, 2024 - ai.nejm.org
Background Timely diagnosis of ST-elevation myocardial infarction (STEMI) is crucial for the
treatment of patients with acute coronary syndrome. Artificial intelligence–enabled …

Point-of-care artificial intelligence-enabled ECG for dyskalemia: A retrospective cohort analysis for accuracy and outcome prediction

C Lin, T Chau, CS Lin, HS Shang, WH Fang… - NPJ digital …, 2022 - nature.com
Dyskalemias are common electrolyte disorders associated with high cardiovascular risk.
Artificial intelligence (AI)-assisted electrocardiography (ECG) has been evaluated as an …

Development and validation of deep learning ECG-based prediction of myocardial infarction in emergency department patients

S Gustafsson, D Gedon, E Lampa, AH Ribeiro… - Scientific Reports, 2022 - nature.com
Myocardial infarction diagnosis is a common challenge in the emergency department. In
managed settings, deep learning-based models and especially convolutional deep models …

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 …

Artificial intelligence-enabled electrocardiography predicts left ventricular dysfunction and future cardiovascular outcomes: a retrospective analysis

HY Chen, CS Lin, WH Fang, YS Lou… - Journal of Personalized …, 2022 - mdpi.com
BACKGROUND: The ejection fraction (EF) provides critical information about heart failure
(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 …

Artificial intelligence–assisted electrocardiography for early diagnosis of thyrotoxic periodic paralysis

C Lin, CS Lin, DJ Lee, CC Lee, SJ Chen… - Journal of the …, 2021 - academic.oup.com
Context Thyrotoxic periodic paralysis (TPP) characterized by acute weakness, hypokalemia,
and hyperthyroidism is a medical emergency with a great challenge in early diagnosis since …