A Novel Computer-Aided Approach for Predicting COVID-19 Severity Using Hyperparameters in ResNet50v2 from X-ray Images
Journal Title: International Journal of Experimental Research and Review - Year 2024, Vol 42, Issue 6
Abstract
This research has been globally impacted by COVID-19 virus, which was a very uncommon, highly contagious & dangerous respiratory illness demanding early detection for effective containment and further spread. In this research, we proposed an innovative methodology that utilizes images of X-rays for COVID-19 detection at an early stage. By employing a convolution neural network, we enhance the accuracy performance via using ResNet50v2 using a hyperparameter. The methodology achieves a remarkable accuracy with an average accuracy of 99.12%. This accuracy surpasses other available models based on different deep learning models like VGG, Xception and DenseNet for COVID identification & detection with the help of X-ray images. X-ray scans are now preferably used modality for the identification & detection of COVID-19, given its widespread utilization and effectiveness. However, manual treatment & examination using X-ray images is very challenging, specifically in the field which is facing a limitation of skilled medical staff. Utilization of deep learning models has demonstrated significant potential and effective results in automating the diagnosis for timely identification of COVID with the help of X-ray films. The suggested architecture is specifically developed for timely prediction and analysis of COVID cases employing X-ray films. It firmly believes that this study holds significant potential in alleviating the workload of frontline radiologists, expediting patient diagnosis and treatment, and facilitating pandemic control efforts.
Authors and Affiliations
Rahul Deva, Arvind Dagur
Click Chemistry: copper, ruthenium catalyzed and photoinduced
Click chemistry is an extremely powerful method for covalent conjugation of molecular entities quickly and efficiently. Click chemistry knitted the threads between two different molecular entities that have created inter...
Examining the Pandemic Induced Adoption of E-Learning Through a UTAUT Model Approach
The Covid-19 pandemic's worldwide disruption has significantly impacted many facets of society, including education and learning. This seismic effect results from the urgent need to stop the virus from spreading, which c...
Micro level problems and management of agricultural activities Jagadishnagar village, Magrahat Block -1, South 24 Parganas, West Bengal, India
West Bengal is an agriculture based state of India as its economy is highly dependent on agricultural production. Being situated in the active delta part of Ganga still, there are some problems to cultivate food crop mai...
Systemic Regulatory Abnormalities in Glycemic Control and its Relation with Depression - A Cross-Sectional Study
Globally, depression is the 3rd leading cause of disability-adjusted life years. The presence of depression and its symptoms has been associated with improper control of glucose and poor glycemic index and a bidirection...
A Co-occurrence Network Analysis of research work in supply chain finance and corporate sustainable strategy in Industrial sector
With the increasing significance of supply chain finance and corporate strategies in industrial settings, this study attempts in implementing bibliometric analysis coupled with co-occurrence network visualization as its...