ArticleComputational intelligence and neuroscience2022
ResNet-50 for 12-Lead Electrocardiogram Automated Diagnosis.
Article in Computational intelligence and neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.
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Who cites it
19 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Advances in machine and deep learning for ECG beat classification: a systematic review.Frontiers in digital health · 2025Pooled it
- An ECG foundation model for generalizable cardiac function prediction across the lifespan.medRxiv : the preprint server for health sciences · 2026Article
- Application of deep learning strategies in the standardization and diagnostic efficiency enhancement of chest X-ray imaging.BMC medical imaging · 2026Article
- Time series electrocardiography (ECG) data for early prediction of cardiac arrest.Scientific reports · 2026Article
- A lightweight deep neural network for personalized detecting ventricular arrhythmias from a single-lead ECG device.PLOS digital health · 2025Article
- Deep Convolutional Generative Adversarial Network for Improved Cardiac Image Classification in Heart Disease Diagnosis.Journal of imaging informatics in medicine · 2025Article
- Electrophysiological biomarkers based on CISANET characterize illness severity and suicidal ideation among patients with major depressive disorder.Medical & biological engineering & computing · 2025Article
- Specialized ECG data augmentation method: leveraging precordial lead positional variability.Biomedical engineering letters · 2025Article
- Integrating electrocardiogram and fundus images for early detection of cardiovascular diseases.Scientific reports · 2025Article
- Deep learning assists early-detection of hypertension-mediated heart change on ECG signals.Hypertension research : official journal of the Japanese Society of Hypertension · 2025Article
- A multitask deep learning model utilizing electrocardiograms for major cardiovascular adverse events prediction.NPJ digital medicine · 2025Article
- Predicting troponin biomarker elevation from electrocardiograms using a deep neural network.Open heart · 2024Article
- Artificial intelligence for detection of retinal toxicity in chloroquine and hydroxychloroquine therapy using multifocal electroretinogram waveforms.Scientific reports · 2024Article
- Myocardial scar and left ventricular ejection fraction classification for electrocardiography image using multi-task deep learning.Scientific reports · 2024Article
- Identification of middle cerebral artery stenosis in transcranial Doppler using a modified VGG-16.Frontiers in neurology · 2024Article
- Artificial Intelligence in Cardiology and Atherosclerosis in the Context of Precision Medicine: A Scoping Review.Applied bionics and biomechanics · 2024Article
- Improving diagnosis accuracy with an intelligent image retrieval system for lung pathologies detection: a features extractor approach.Scientific reports · 2023Article
- Automatic Detection of Cracks in Cracked Tooth Based on Binary Classification Convolutional Neural Networks.Applied bionics and biomechanics · 2022Article
- Trust-Based Smart Contract for Automated Agent to Agent Communication.Computational intelligence and neuroscience · 2022Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Nowadays, the implementation of Artificial Intelligence (AI) in medical diagnosis has attracted major attention within both the academic literature and industrial sector. AI would include deep learning (DL) models, where these models have been achieving a spectacular performance in healthcare applications. According to the World Health Organization (WHO), in 2020 there were around 25.6 million people who died from cardiovascular diseases (CVD). Thus, this paper aims to shad the light on cardiology since it is widely considered as one of the most important in medicine field. The paper develops an efficient DL model for automatic diagnosis of 12-lead electrocardiogram (ECG) signals with 27 classes, including 26 types of CVD and a normal sinus rhythm. The proposed model consists of Residual Neural Network (ResNet-50). An experimental work has been conducted using combined public databases from the USA, China, and Germany as a proof-of-concept. Simulation results of the proposed model have achieved an accuracy of 97.63% and a precision of 89.67%. The achieved results are validated against the actual values in the recent literature.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.