A survey on physical unclonable function (PUF)-based security solutions for Internet of Things
The vast areas of applications for IoTs in future smart cities, smart transportation systems,
and so on represent a thriving surface for several security attacks with economic …
and so on represent a thriving surface for several security attacks with economic …
Review of deep learning-based atrial fibrillation detection studies
Atrial fibrillation (AF) is a common arrhythmia that can lead to stroke, heart failure, and
premature death. Manual screening of AF on electrocardiography (ECG) is time-consuming …
premature death. Manual screening of AF on electrocardiography (ECG) is time-consuming …
Explainable AI for clinical and remote health applications: a survey on tabular and time series data
Abstract Nowadays Artificial Intelligence (AI) has become a fundamental component of
healthcare applications, both clinical and remote, but the best performing AI systems are …
healthcare applications, both clinical and remote, but the best performing AI systems are …
Designing ECG monitoring healthcare system with federated transfer learning and explainable AI
Deep learning plays a vital role in classifying different arrhythmias using
electrocardiography (ECG) data. Nevertheless, training deep learning models normally …
electrocardiography (ECG) data. Nevertheless, training deep learning models normally …
A survey on the interpretability of deep learning in medical diagnosis
Deep learning has demonstrated remarkable performance in the medical domain, with
accuracy that rivals or even exceeds that of human experts. However, it has a significant …
accuracy that rivals or even exceeds that of human experts. However, it has a significant …
AFCNNet: Automated detection of AF using chirplet transform and deep convolutional bidirectional long short term memory network with ECG signals
Atrial fibrillation (AF) is the most common type of cardiac arrhythmia and is characterized by
the heart's beating in an uncoordinated manner. In clinical studies, patients often do not …
the heart's beating in an uncoordinated manner. In clinical studies, patients often do not …
[HTML][HTML] State-of-the-art deep learning methods on electrocardiogram data: systematic review
Background Electrocardiogram (ECG) is one of the most common noninvasive diagnostic
tools that can provide useful information regarding a patient's health status. Deep learning …
tools that can provide useful information regarding a patient's health status. Deep learning …
Afibri-net: A lightweight convolution neural network based atrial fibrillation detector
By considering limited resource-constraints of medical devices and advanced deep learning
networks, in this paper, we explore a lightweight convolutional neural network (CNN) based …
networks, in this paper, we explore a lightweight convolutional neural network (CNN) based …
How machine learning is impacting research in atrial fibrillation: implications for risk prediction and future management
There has been an exponential growth of artificial intelligence (AI) and machine learning
(ML) publications aimed at advancing our understanding of atrial fibrillation (AF), which has …
(ML) publications aimed at advancing our understanding of atrial fibrillation (AF), which has …
Machine learning in the detection and management of atrial fibrillation
FK Wegner, L Plagwitz, F Doldi, C Ellermann… - Clinical Research in …, 2022 - Springer
Abstract Machine learning has immense novel but also disruptive potential for medicine.
Numerous applications have already been suggested and evaluated concerning …
Numerous applications have already been suggested and evaluated concerning …