[HTML][HTML] Application of Transfer Learning for Biomedical Signals: A Comprehensive Review of the Last Decade (2014-2024)
Precise and timely disease diagnosis is essential for making effective treatment decisions
and halting disease progression. Biomedical signals offer the potential for non-invasive …
and halting disease progression. Biomedical signals offer the potential for non-invasive …
Improving pneumonia detection in chest X-rays using transfer learning approach (AlexNet) and adversarial training
The method outlined in this paper employs transfer learning and adversarial training to
enhance the precision of pneumonia identification in chest X-rays. The authors use the …
enhance the precision of pneumonia identification in chest X-rays. The authors use the …
Transfer learning for improved electrocardiogram diagnosis of cardiac disease: exploring the potential of pre-trained models
Predicting the onset of cardiovascular disease (CVD) has been a hot topic for researchers
for years, and recently, the concept of transfer learning has been gaining traction in this field …
for years, and recently, the concept of transfer learning has been gaining traction in this field …
Development and validation of embedded device for electrocardiogram arrhythmia empowered with transfer learning
With the emergence of the Internet of Things (IoT), investigation of different diseases in
healthcare improved, and cloud computing helped to centralize the data and to access …
healthcare improved, and cloud computing helped to centralize the data and to access …
Scalar invariant transform based deep learning framework for detecting heart failures using ECG signals
Heart diseases are leading to death across the globe. Exact detection and treatment for
heart disease in its early stages could potentially save lives. Electrocardiogram (ECG) is one …
heart disease in its early stages could potentially save lives. Electrocardiogram (ECG) is one …
[HTML][HTML] GAN-SkipNet: a solution for data imbalance in cardiac arrhythmia detection using electrocardiogram signals from a benchmark dataset
Electrocardiography (ECG) plays a pivotal role in monitoring cardiac health, yet the manual
analysis of ECG signals is challenging due to the complex task of identifying and …
analysis of ECG signals is challenging due to the complex task of identifying and …
Novel interpretable Feature set extraction and classification for accurate atrial fibrillation detection from ECGs
Objective We present a novel method for detecting atrial fibrillation (AFib) by analyzing Lead
II electrocardiograms (ECGs) using a unique set of features. Methods For this purpose, we …
II electrocardiograms (ECGs) using a unique set of features. Methods For this purpose, we …
HRIDM: Hybrid Residual/Inception-Based Deeper Model for Arrhythmia Detection from Large Sets of 12-Lead ECG Recordings
Heart diseases such as cardiovascular and myocardial infarction are the foremost reasons
of death in the world. The timely, accurate, and effective prediction of heart diseases is …
of death in the world. The timely, accurate, and effective prediction of heart diseases is …
[PDF][PDF] Spam and Sentiment Detection in Arabic Tweets Using MARBERT Model.
A Alotaibi, A Rahman, R Alhaza… - Mathematical …, 2022 - researchgate.net
Accepted: 4 October 2022 Saudi Telecom Company (STC) is among the most popular
companies in Saudi Arabia, with many customers. Yet, there is still a big room for …
companies in Saudi Arabia, with many customers. Yet, there is still a big room for …
[PDF][PDF] An Overview of Self-Adaptive Differential Evolution Algorithms with Mutation Strategy.
D AlKhulaifi, M AlQahtani, Z AlSadeq… - Mathematical …, 2022 - researchgate.net
Received: 24 Janurary 2022 Accepted: 2 August 2022 Differential Evolution (DE) is a widely
used global searching algorithm that solves realworld optimization problems. It is …
used global searching algorithm that solves realworld optimization problems. It is …