A 76-year-old woman presents with a persistently rapid heart rate that she attributes to her pacemaker. What does the ECG show?

Dr. George Shaker has huge hopes for a small radar device he developed with a team of researchers at the University of ...

The following is a summary of “Continuous quality improvement for prehospital STEMI improved triage rates and achievement of ...

Research has linked higher levels of air pollution to the risk of acute myocardial infarctions, or heart attacks. How these ...

Abstract: Myocardial infarction (MI) is one of the most dangerous cardiovascular diseases, typically diagnosed using electrocardiogram (ECG). While many deep learning methods exist for MI detection, ...

Yangtze Delta Region Academy of Beijing Institute of Technology, Jiaxing 314011, PR China Key Laboratory of Intelligent Sensing Materials and Chip Integration Technology of Zhejiang Province, Hangzhou ...

Abstract: A myocardial infarction (MI) can be fatal and cause irreversible damage ... automated or manual inspection by experts with the help of an electrocardiogram (ECG). Manual detection is ...

(American Journal of Human Genetics) An artificial intelligence (AI)-enhanced ECG model was able to detect acute myocardial infarction and predict 30-day major adverse cardiovascular events in a ...

She returns for a follow-up visit for palpitations, and a 12-lead ECG is obtained. The rhythm is regular, at a rate of 150 beats/min. The QRS complex duration is normal (0.08 sec) with normal ...

Objective To evaluate the association between contemporary hormonal contraceptive use and the risk of incident ischaemic stroke and myocardial infarction. Design Real-world, nationwide, prospective ...

This illustrates that DL research in the context of myocardial infarction primarily involves the use of machine learning techniques to extract ECG features for predicting and diagnosing risks and ...

We sought to pilot the collection of heart rate variability data from the Apple Watch electrocardiograph (ECG) sensor and apply machine learning techniques to develop a stress prediction tool. Random ...