Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Electrocardiogram

Electrocardiogram

An electrocardiogram (ECG or EKG) is a critical diagnostic tool that records the electrical signals produced by the heart during each heartbeat. This recording is achieved through electrodes placed strategically on the arms, legs, and chest. The electrocardiograph amplifies these signals and produces 12 distinct tracings, offering a comprehensive understanding of the heart's electrical activity.
Three major waveforms are present in a typical ECG recording: the P wave, the QRS complex, and...

Acute Coronary Syndrome III: Diagnostic Studies

Acute Coronary Syndrome III: Diagnostic Studies

Diagnosing acute coronary syndrome or ACS begins with a thorough patient history. Notable symptoms include central, crushing chest pain radiating to the left arm, neck, jaw, or back, along with shortness of breath, sweating (diaphoresis), nausea, vomiting, dizziness, and palpitations.It is crucial to note any history of cardiac illnesses and assess risk factors, including age, gender, smoking, hypertension, diabetes, hyperlipidemia, and a sedentary lifestyle.During physical examination, vital...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Incidental Tentorial Cerebelli Hypoplasia: A Case Report and Comprehensive Literature Review of Its Clinical and Imaging Characteristics.

Case reports in medicine·2026

Same author

Antioxidant, antimicrobial, and AMPA receptor modulatory activities of selected medicinal plant extracts reveal multitarget pharmacological potential.

Scientific reports·2026

Same author

Primary Hepatoid Adenocarcinoma of the Lung With Signet Ring Cell Differentiation and Widespread Osseous Metastases: A Case Report.

Respirology case reports·2026

Same author

Temporal trends and disparities in acute ischemic event mortality among U.S. adults with coexisting atherosclerotic heart disease and diabetes mellitus: A national analysis.

Journal of investigative medicine : the official publication of the American Federation for Clinical Research·2026

Same author

Iatrogenic Kaposi Sarcoma in an HIV-Negative Patient With Immune Thrombocytopenic Purpura Treated With Rituximab and Corticosteroids: A Fatal Extracutaneous Presentation.

Cancer reports (Hoboken, N.J.)·2026

Same author

National trends and disparities in Alzheimer disease's mortality (1999-2023) with scenario projections and a data-driven LSTM sensitivity analysis to 2043.

European archives of psychiatry and clinical neuroscience·2026

Search research articles

Related Experiment Video

Updated: Jan 15, 2026

Real-Time Cardiac Mapping with a Noninvasive Imageless Electrocardiographic Imaging System

Real-Time Cardiac Mapping with a Noninvasive Imageless Electrocardiographic Imaging System

Published on: April 11, 2025

Artificial Intelligence for Myocardial Infarction Detection via Electrocardiogram: A Scoping Review.

Sosana Bdir¹, Mennatallah Jaber¹, Osaid Tanbouz¹

¹Department of Medicine, Faculty of Medicine and Allied Health Sciences, An-Najah National University, Nablus P400, Palestine.

Journal of Clinical Medicine

|October 16, 2025

Summary

Artificial intelligence (AI) shows promise for detecting myocardial infarction (MI) using electrocardiograms (ECGs). However, current AI diagnostic performance is limited by dataset and validation issues, necessitating standardization for reliable clinical use.

Keywords:

12-lead ECG CNN artificial intelligence detection myocardial infarction

More Related Videos

A Research Method For Detecting Transient Myocardial Ischemia In Patients With Suspected Acute Coronary Syndrome Using Continuous ST-segment Analysis

A Research Method For Detecting Transient Myocardial Ischemia In Patients With Suspected Acute Coronary Syndrome Using Continuous ST-segment Analysis

Published on: December 28, 2012

Author Spotlight: A Novel Standardized Technique for Real-Time Biomedical Imaging of Acute Myocardial Injury

Author Spotlight: A Novel Standardized Technique for Real-Time Biomedical Imaging of Acute Myocardial Injury

Published on: March 22, 2024

Related Experiment Videos

Last Updated: Jan 15, 2026

Real-Time Cardiac Mapping with a Noninvasive Imageless Electrocardiographic Imaging System

Real-Time Cardiac Mapping with a Noninvasive Imageless Electrocardiographic Imaging System

Published on: April 11, 2025

A Research Method For Detecting Transient Myocardial Ischemia In Patients With Suspected Acute Coronary Syndrome Using Continuous ST-segment Analysis

A Research Method For Detecting Transient Myocardial Ischemia In Patients With Suspected Acute Coronary Syndrome Using Continuous ST-segment Analysis

Published on: December 28, 2012

Author Spotlight: A Novel Standardized Technique for Real-Time Biomedical Imaging of Acute Myocardial Injury

Author Spotlight: A Novel Standardized Technique for Real-Time Biomedical Imaging of Acute Myocardial Injury

Published on: March 22, 2024

Area of Science:

Cardiology
Artificial Intelligence
Medical Diagnostics

Background:

Acute myocardial infarction (MI) remains a leading cause of mortality globally, posing significant healthcare challenges.
Early and accurate MI detection is crucial but often difficult despite diagnostic advancements.
Artificial intelligence (AI) is emerging as a powerful tool to enhance electrocardiogram (ECG)-based MI detection.

Purpose of the Study:

To systematically map and evaluate the applications of AI in detecting MI using ECG data.
To provide a comprehensive overview of AI-driven MI detection methods.
To identify trends and challenges in AI for ECG-based MI diagnosis.

Main Methods:

A systematic scoping review of AI applications for MI detection via ECG.
Searches conducted in major databases (MEDLINE, Embase, Web of Science, Cochrane) from 2015 to October 2024.
Inclusion of 220 studies following PRISMA-ScR guidelines, extracting data on AI models, algorithms, ECG types, and performance metrics.

Main Results:

AI applications for MI detection have rapidly increased since 2015, peaking in 2022.
Convolutional neural networks and support vector machines were predominant AI models, often using 12-lead ECGs.
High reported performance metrics were often based on small, single-source datasets with optimistic validation, showing limited generalizability and potential biases.

Conclusions:

AI-based MI detection using ECGs is a rapidly growing field.
Current diagnostic performance is significantly constrained by dataset limitations and validation methodologies.
Standardization in reporting, datasets, and validation is essential for clinical integration, explainability, and equitable deployment of AI in MI detection.