Machine-learning-based disease diagnosis: A comprehensive review
MM Ahsan, SA Luna, Z Siddique - Healthcare, 2022 - mdpi.com
Globally, there is a substantial unmet need to diagnose various diseases effectively. The
complexity of the different disease mechanisms and underlying symptoms of the patient …
complexity of the different disease mechanisms and underlying symptoms of the patient …
Machine learning-based heart disease diagnosis: A systematic literature review
MM Ahsan, Z Siddique - Artificial Intelligence in Medicine, 2022 - Elsevier
Heart disease is one of the significant challenges in today's world and one of the leading
causes of many deaths worldwide. Recent advancement of machine learning (ML) …
causes of many deaths worldwide. Recent advancement of machine learning (ML) …
Performance of deep learning vs machine learning in plant leaf disease detection
Plants are recognized as essential as they are the primary source of humanity's energy
production since they are having nutritious, medicinal, etc. values. At any time between crop …
production since they are having nutritious, medicinal, etc. values. At any time between crop …
A review of principal component analysis algorithm for dimensionality reduction
BMS Hasan, AM Abdulazeez - Journal of Soft Computing …, 2021 - publisher.uthm.edu.my
Big databases are increasingly widespread and are therefore hard to understand, in
exploratory biomedicine science, big data in health research is highly exciting because data …
exploratory biomedicine science, big data in health research is highly exciting because data …
A transformer-based deep neural network for arrhythmia detection using continuous ECG signals
R Hu, J Chen, L Zhou - Computers in Biology and Medicine, 2022 - Elsevier
Recently, much effort has been put into solving arrhythmia classification problems with
machine learning-based methods. However, inter-heartbeat dependencies have been …
machine learning-based methods. However, inter-heartbeat dependencies have been …
Arrhythmia detection using deep convolutional neural network with long duration ECG signals
This article presents a new deep learning approach for cardiac arrhythmia (17 classes)
detection based on long-duration electrocardiography (ECG) signal analysis …
detection based on long-duration electrocardiography (ECG) signal analysis …
A new approach for arrhythmia classification using deep coded features and LSTM networks
Background and objective For diagnosis of arrhythmic heart problems, electrocardiogram
(ECG) signals should be recorded and monitored. The long-term signal records obtained …
(ECG) signals should be recorded and monitored. The long-term signal records obtained …
[PDF][PDF] Novel deep genetic ensemble of classifiers for arrhythmia detection using ECG signals
P Pławiak, UR Acharya - Neural Comput. Appl, 2020 - researchgate.net
The heart disease is one of the most serious health problems in today's world. Over 50
million persons have cardiovascular diseases around the world. Our proposed work based …
million persons have cardiovascular diseases around the world. Our proposed work based …
Applying artificial intelligence to wearable sensor data to diagnose and predict cardiovascular disease: a review
Cardiovascular disease (CVD) is the world's leading cause of mortality. There is significant
interest in using Artificial Intelligence (AI) to analyse data from novel sensors such as …
interest in using Artificial Intelligence (AI) to analyse data from novel sensors such as …
Generalization of convolutional neural networks for ECG classification using generative adversarial networks
Electrocardiograms (ECGs) play a vital role in the clinical diagnosis of heart diseases. An
ECG record of the heart signal over time can be used to discover numerous arrhythmias. Our …
ECG record of the heart signal over time can be used to discover numerous arrhythmias. Our …