[HTML][HTML] Application of deep learning techniques in diagnosis of covid-19 (coronavirus): a systematic review

YH Bhosale, KS Patnaik - Neural processing letters, 2023 - Springer
Covid-19 is now one of the most incredibly intense and severe illnesses of the twentieth
century. Covid-19 has already endangered the lives of millions of people worldwide due to …

[HTML][HTML] A comparative study of X-ray and CT images in COVID-19 detection using image processing and deep learning techniques

HM Shyni, E Chitra - Computer Methods and Programs in Biomedicine …, 2022 - Elsevier
The deadly coronavirus has not just devastated the lives of millions but has put the entire
healthcare system under tremendous pressure. Early diagnosis of COVID-19 plays a …

A lightweight CNN-based network on COVID-19 detection using X-ray and CT images

ML Huang, YC Liao - Computers in Biology and Medicine, 2022 - Elsevier
Background and objectives The traditional method of detecting COVID-19 disease mainly
rely on the interpretation of computer tomography (CT) or X-ray images (X-ray) by doctors or …

Detection of COVID-19 using deep learning techniques and classification methods

Ç Oğuz, M Yağanoğlu - Information Processing & Management, 2022 - Elsevier
Since the patient is not quarantined during the conclusion of the Polymerase Chain
Reaction (PCR) test used in the diagnosis of COVID-19, the disease continues to spread. In …

[HTML][HTML] Role of artificial intelligence in COVID-19 detection

A Gudigar, U Raghavendra, S Nayak, CP Ooi… - Sensors, 2021 - mdpi.com
The global pandemic of coronavirus disease (COVID-19) has caused millions of deaths and
affected the livelihood of many more people. Early and rapid detection of COVID-19 is a …

[HTML][HTML] Feature extraction using a residual deep convolutional neural network (ResNet-152) and optimized feature dimension reduction for MRI brain tumor …

S Athisayamani, RS Antonyswamy, V Sarveshwaran… - Diagnostics, 2023 - mdpi.com
One of the top causes of mortality in people globally is a brain tumor. Today, biopsy is
regarded as the cornerstone of cancer diagnosis. However, it faces difficulties, including low …

[HTML][HTML] A hybrid convolutional neural network model for diagnosis of COVID-19 using chest X-ray images

P Kaur, S Harnal, R Tiwari, FS Alharithi… - International Journal of …, 2021 - mdpi.com
COVID-19 declared as a pandemic that has a faster rate of infection and has impacted the
lives and the country's economy due to forced lockdowns. Its detection using RT-PCR is …

McS-Net: Multi-class Siamese network for severity of COVID-19 infection classification from lung CT scan slices

S Ahuja, BK Panigrahi, N Dey, A Taneja… - Applied Soft Computing, 2022 - Elsevier
Worldwide COVID-19 is a highly infectious and rapidly spreading disease in almost all age
groups. The Computed Tomography (CT) scans of lungs are found to be accurate for the …

[HTML][HTML] Explainable artificial intelligence approach in combating real-time surveillance of COVID19 pandemic from CT scan and X-ray images using ensemble model

F Ullah, J Moon, H Naeem, S Jabbar - The Journal of Supercomputing, 2022 - Springer
Population size has made disease monitoring a major concern in the healthcare system,
due to which auto-detection has become a top priority. Intelligent disease detection …

SocialSense: Mobile crowd sensing-based physical distance monitoring model leveraging federated learning for pandemic

D De, S Ghosh, A Mukherjee - Internet of Things, 2023 - Elsevier
As recommended by the World Health Organization, testing, isolation, and physical
distancing are the keys to combat the pandemic due to COVID-19. However, physical …