Opportunities and challenges of deep learning methods for electrocardiogram data: A systematic review
Background The electrocardiogram (ECG) is one of the most commonly used diagnostic
tools in medicine and healthcare. Deep learning methods have achieved promising results …
tools in medicine and healthcare. Deep learning methods have achieved promising results …
Transfer learning for ECG classification
K Weimann, TOF Conrad - Scientific reports, 2021 - nature.com
Remote monitoring devices, which can be worn or implanted, have enabled a more effective
healthcare for patients with periodic heart arrhythmia due to their ability to constantly monitor …
healthcare for patients with periodic heart arrhythmia due to their ability to constantly monitor …
Automating detection and localization of myocardial infarction using shallow and end-to-end deep neural networks
Myocardial infarction (MI), also known as a heart attack, is one of the common cardiac
disorders caused by prolonged myocardial ischemia. For MI patients, specifying the exact …
disorders caused by prolonged myocardial ischemia. For MI patients, specifying the exact …
Deep learning based feature engineering to detect anterior and inferior myocardial infarction using uwb radar data
Cardiovascular disease is the main cause of death worldwide. The World Health
Organization (WHO) reports that 17.9 million individuals die yearly due to complications from …
Organization (WHO) reports that 17.9 million individuals die yearly due to complications from …
Enhancing diagnosis of anterior and inferior myocardial infarctions using UWB radar and AI-driven feature fusion approach
Despite significant improvement in prognosis, myocardial infarction (MI) remains a major
cause of morbidity and mortality around the globe. MI is a life-threatening cardiovascular …
cause of morbidity and mortality around the globe. MI is a life-threatening cardiovascular …
DDxNet: a deep learning model for automatic interpretation of electronic health records, electrocardiograms and electroencephalograms
Effective patient care mandates rapid, yet accurate, diagnosis. With the abundance of non-
invasive diagnostic measurements and electronic health records (EHR), manual …
invasive diagnostic measurements and electronic health records (EHR), manual …
Application of convolutional dendrite net for detection of myocardial infarction using ecg signals
X Ma, X Fu, Y Sun, N Wang, Y Gao - IEEE Sensors Journal, 2022 - ieeexplore.ieee.org
Myocardial infarction (MI) is a sudden-onset medical emergency. Without timely diagnosis
and treatment, mortality is very high. The mining of deep features increases the …
and treatment, mortality is very high. The mining of deep features increases the …
Hybridization of Artificial Neural Network with Spotted Hyena Optimization (SHO) Algorithm for Heart Disease Detection
Heart‐related illnesses are the leading cause of mortality globally, which causes a high
number of deaths in poor‐and middle‐income nations like India. Large amounts of data are …
number of deaths in poor‐and middle‐income nations like India. Large amounts of data are …
Effective prior selection and knowledge transfer for deep learning applications
S Katoch - 2022 - search.proquest.com
In the recent years, deep learning has gained popularity for its ability to be utilized for
several computer vision applications without any apriori knowledge. However, to introduce …
several computer vision applications without any apriori knowledge. However, to introduce …
Convolutional dendrite net detects myocardial infarction based on ecg signal measured by flexible sensor
X Ma, X Fu, Y Sun, N Wang, X Ning… - 2021 IEEE International …, 2021 - ieeexplore.ieee.org
Myocardial infarction (MI) is a kind of heart disease with high mortality, which is caused by
long-term myocardial ischemia. To diagnosis MI automatically, an automatic detection …
long-term myocardial ischemia. To diagnosis MI automatically, an automatic detection …