Artificial intelligence in disease diagnosis: a systematic literature review, synthesizing framework and future research agenda
Artificial intelligence can assist providers in a variety of patient care and intelligent health
systems. Artificial intelligence techniques ranging from machine learning to deep learning …
systems. Artificial intelligence techniques ranging from machine learning to deep learning …
CNN variants for computer vision: History, architecture, application, challenges and future scope
Computer vision is becoming an increasingly trendy word in the area of image processing.
With the emergence of computer vision applications, there is a significant demand to …
With the emergence of computer vision applications, there is a significant demand to …
Automated detection of COVID-19 cases using deep neural networks with X-ray images
Abstract The novel coronavirus 2019 (COVID-2019), which first appeared in Wuhan city of
China in December 2019, spread rapidly around the world and became a pandemic. It has …
China in December 2019, spread rapidly around the world and became a pandemic. It has …
[PDF][PDF] Detection of coronavirus disease (covid-19) based on deep features
The detection of coronavirus (COVID-19) is now a critical task for the medical practitioner.
The coronavirus spread so quickly between people and approaches 100,000 people …
The coronavirus spread so quickly between people and approaches 100,000 people …
Evaluation of artificial intelligence techniques in disease diagnosis and prediction
A broad range of medical diagnoses is based on analyzing disease images obtained
through high-tech digital devices. The application of artificial intelligence (AI) in the …
through high-tech digital devices. The application of artificial intelligence (AI) in the …
A review on transfer learning in EEG signal analysis
Electroencephalogram (EEG) signal analysis, which is widely used for human-computer
interaction and neurological disease diagnosis, requires a large amount of labeled data for …
interaction and neurological disease diagnosis, requires a large amount of labeled data for …
Deep learning in ECG diagnosis: A review
X Liu, H Wang, Z Li, L Qin - Knowledge-Based Systems, 2021 - Elsevier
Cardiovascular disease (CVD) is a general term for a series of heart or blood vessels
abnormality that serves as a global leading reason for death. The earlier the abnormal heart …
abnormality that serves as a global leading reason for death. The earlier the abnormal heart …
[HTML][HTML] A review on deep learning methods for ECG arrhythmia classification
Deep Learning (DL) has recently become a topic of study in different applications including
healthcare, in which timely detection of anomalies on Electrocardiogram (ECG) can play a …
healthcare, in which timely detection of anomalies on Electrocardiogram (ECG) can play a …
A survey of the recent architectures of deep convolutional neural networks
Abstract Deep Convolutional Neural Network (CNN) is a special type of Neural Networks,
which has shown exemplary performance on several competitions related to Computer …
which has shown exemplary performance on several competitions related to Computer …
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 …