AIMC Topic: Myocardial Infarction
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Evolution of single-lead ECG for STEMI detection using a deep learning approach.
International journal of cardiology
Nov 18, 2021
BACKGROUND: While ST-Elevation Myocardial Infarction (STEMI) door-to-balloon times are often below 90 min, symptom to door times remain long at 2.5-h, due at least in part to a delay in diagnosis.
Rational and design of ST-segment elevation not associated with acute cardiac necrosis (LESTONNAC). A prospective registry for validation of a deep learning system assisted by artificial intelligence.
Journal of electrocardiology
Oct 30, 2021
BACKGROUND: Patients with chest pain and persistent ST segment elevation (STE) may not have acute coronary occlusions or serum troponin curves suggestive of acute necrosis. Our objective is the validation and cost-effectiveness analysis of a diagnost...
Multitask Interactive Attention Learning Model Based on Hand Images for Assisting Chinese Medicine in Predicting Myocardial Infarction.
Computational and mathematical methods in medicine
Oct 26, 2021
Acute myocardial infarction (AMI) is one of the most serious and dangerous cardiovascular diseases. In recent years, the number of patients around the world has been increasing significantly, among which people under the age of 45 have become the hig...
ML-Net: Multi-Channel Lightweight Network for Detecting Myocardial Infarction.
IEEE journal of biomedical and health informatics
Oct 5, 2021
Due to the complexity of myocardial infarction (MI) waveform, most traditional automatic diagnosis models rarely detect it, while those able to detect MI often require high computing and storage capacity, rendering them unsuitable for portable device...
Real-time frequency-independent single-Lead and single-beat myocardial infarction detection.
Artificial intelligence in medicine
Oct 1, 2021
This study proposes a novel real-time frequency-independent myocardial infarction detector for Lead II electrocardiograms. The underlying Deep-LSTM network is trained using the PTB-XL database, the largest to date publicly available electrocardiograp...
Automated Detection of Acute Myocardial Infarction Using Asynchronous Electrocardiogram Signals-Preview of Implementing Artificial Intelligence With Multichannel Electrocardiographs Obtained From Smartwatches: Retrospective Study.
Journal of medical Internet research
Sep 10, 2021
BACKGROUND: When using a smartwatch to obtain electrocardiogram (ECG) signals from multiple leads, the device has to be placed on different parts of the body sequentially. The ECG signals measured from different leads are asynchronous. Artificial int...
A Deep Learning Approach to Predict Diabetes' Cardiovascular Complications From Administrative Claims.
IEEE journal of biomedical and health informatics
Sep 3, 2021
People with diabetes require lifelong access to healthcare services to delay the onset of complications. Their disease management processes generate great volumes of data across several domains, from clinical to administrative. Difficulties in access...
Applications of machine learning to undifferentiated chest pain in the emergency department: A systematic review.
PloS one
Aug 24, 2021
BACKGROUND: Chest pain is amongst the most common reason for presentation to the emergency department (ED). There are many causes of chest pain, and it is important for the emergency physician to quickly and accurately diagnose life threatening cause...
Deep Learning-Based Measurement of Total Plaque Area in B-Mode Ultrasound Images.
IEEE journal of biomedical and health informatics
Aug 5, 2021
Measurement of total-plaque-area (TPA) is important for determining long term risk for stroke and monitoring carotid plaque progression. Since delineation of carotid plaques is required, a deep learning method can provide automatic plaque segmentatio...
Machine Learning with F-Sodium Fluoride PET and Quantitative Plaque Analysis on CT Angiography for the Future Risk of Myocardial Infarction.
Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Apr 23, 2021
Coronary F-sodium fluoride (F-NaF) PET and CT angiography-based quantitative plaque analysis have shown promise in refining risk stratification in patients with coronary artery disease. We combined both of these novel imaging approaches to develop an...
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