Lightweight deep CNN-based models for early detection of COVID-19 patients from chest X-ray images
Hundreds of millions of people worldwide have recently been infected by the novel
Coronavirus disease (COVID-19), causing significant damage to the health, economy, and …
Coronavirus disease (COVID-19), causing significant damage to the health, economy, and …
[HTML][HTML] An in-depth analysis of Convolutional Neural Network architectures with transfer learning for skin disease diagnosis
Low contrasts and visual similarity between different skin conditions make skin disease
recognition a challenging task. Current techniques to detect and diagnose skin disease …
recognition a challenging task. Current techniques to detect and diagnose skin disease …
DBM-ViT: A multiscale features fusion algorithm for health status detection in CXR/CT lungs images
Y Hao, C Zhang, X Li - Biomedical Signal Processing and Control, 2024 - Elsevier
COVID-19 is a severe acute respiratory syndrome caused by SARS-CoV-2. It is highly
contagious and spreads rapidly around the world. Although reverse transcription …
contagious and spreads rapidly around the world. Although reverse transcription …
[HTML][HTML] Diagnosis of patellofemoral osteoarthritis using enhanced sequential deep learning techniques
The surface electromyography (sEMG) signal is a complex interference pattern resulting
from the electrical activity of contracting muscles, which directly correlates with muscle …
from the electrical activity of contracting muscles, which directly correlates with muscle …
[HTML][HTML] A clinical site workload prediction model with machine learning lifecycle
In clinical trial monitoring, substantial resources are allocated to perform source data
verification (SDV). SDV ensures accurate and reliable transcription of trial participant …
verification (SDV). SDV ensures accurate and reliable transcription of trial participant …
Enhancing multiclass COVID-19 prediction with ESN-MDFS: Extreme smart network using mean dropout feature selection technique
Deep learning and artificial intelligence offer promising tools for improving the accuracy and
efficiency of diagnosing various lung conditions using portable chest x-rays (CXRs). This …
efficiency of diagnosing various lung conditions using portable chest x-rays (CXRs). This …
: a novel deep learning based technique for identifying COVID-19 using images of chest x-ray
U Acharya, S Banerjea - Multimedia Tools and Applications, 2024 - Springer
COVID-19 has affected more than 520 million population worldwide by April 2022. Few
medical examinations such as rapid antigen and RT-PCR are recommended for timely …
medical examinations such as rapid antigen and RT-PCR are recommended for timely …
CNN-O-ELMNet: Optimized Lightweight and Generalized Model for Lung Disease Classification and Severity Assessment
The high burden of lung diseases on healthcare necessitates effective detection methods.
Current Computer-aided design (CAD) systems are limited by their focus on specific …
Current Computer-aided design (CAD) systems are limited by their focus on specific …
A high-accuracy lightweight network model for X-ray image diagnosis: A case study of COVID detection
S Wang, J Ren, X Guo - PloS one, 2024 - journals.plos.org
The Coronavirus Disease 2019 (COVID-19) has caused widespread and significant harm
globally. In order to address the urgent demand for a rapid and reliable diagnostic approach …
globally. In order to address the urgent demand for a rapid and reliable diagnostic approach …
[HTML][HTML] Optimized early fusion of handcrafted and deep learning descriptors for voice pathology detection and classification
R Jegan, R Jayagowri - Healthcare Analytics, 2024 - Elsevier
This study presents an automated noninvasive voice disorder detection and classification
approach using an optimized fusion of modified glottal source estimation and deep transfer …
approach using an optimized fusion of modified glottal source estimation and deep transfer …