Deep transfer learning approaches to predict glaucoma, cataract, choroidal neovascularization, diabetic macular edema, drusen and healthy eyes: an experimental …

Y Kumar, S Gupta - Archives of Computational Methods in Engineering, 2023 - Springer
Artificial intelligence (AI) has lately witnessed an age of tremendous expansion across
several industries, including healthcare. In recent years, substantial advancements in AI …

A Survey of Deep Learning Techniques for the Analysis of COVID-19 and their usability for Detecting Omicron

A Khan, SH Khan, M Saif, A Batool… - … of Experimental & …, 2024 - Taylor & Francis
ABSTRACT The Coronavirus (COVID-19) outbreak in December 2019 has drastically
affected humans worldwide, creating a health crisis that has infected millions of lives and …

Screening of COVID-19 suspected subjects using multi-crossover genetic algorithm based dense convolutional neural network

D Singh, V Kumar, M Kaur, MY Jabarulla… - IEEE Access, 2021 - ieeexplore.ieee.org
Fast and accurate screening of novel coronavirus (COVID-19) suspected subjects plays a
vital role in timely quarantine and medical care. Deep transfer learning-based screening …

Real‐Time Implementation of AI‐Based Face Mask Detection and Social Distancing Measuring System for COVID‐19 Prevention

S Teboulbi, S Messaoud, MA Hajjaji… - Scientific …, 2021 - Wiley Online Library
Since the infectious coronavirus disease (COVID‐19) was first reported in Wuhan, it has
become a public health problem in China and even around the world. This pandemic is …

Machine learning-based research for COVID-19 detection, diagnosis, and prediction: A survey

Y Meraihi, AB Gabis, S Mirjalili, A Ramdane-Cherif… - SN computer …, 2022 - Springer
The year 2020 experienced an unprecedented pandemic called COVID-19, which impacted
the whole world. The absence of treatment has motivated research in all fields to deal with it …

Understanding basic principles of Artificial Intelligence: a practical guide for intensivists

V Bellini, M Cascella, F Cutugno… - Acta Bio Medica …, 2022 - pmc.ncbi.nlm.nih.gov
Background and aim: Artificial intelligence was born to allow computers to learn and control
their environment, trying to imitate the human brain structure by simulating its biological …

Smart flood detection with AI and blockchain integration in Saudi Arabia using drones

A Alsumayt, N El-Haggar, L Amouri, ZM Alfawaer… - Sensors, 2023 - mdpi.com
Global warming and climate change are responsible for many disasters. Floods pose a
serious risk and require immediate management and strategies for optimal response times …

Supervised and weakly supervised deep learning models for COVID-19 CT diagnosis: A systematic review

H Hassan, Z Ren, C Zhou, MA Khan, Y Pan… - Computer Methods and …, 2022 - Elsevier
Artificial intelligence (AI) and computer vision (CV) methods become reliable to extract
features from radiological images, aiding COVID-19 diagnosis ahead of the pathogenic tests …

Coronavirus disease (COVID-19) detection using X-ray images and enhanced DenseNet

S Albahli, N Ayub, M Shiraz - Applied Soft Computing, 2021 - Elsevier
Abstract The 2019 novel coronavirus (COVID-19) originating from China, has spread rapidly
among people living in other countries. According to the World Health Organization (WHO) …

Diagnosis of coronavirus disease from chest X-ray images using DenseNet-169 architecture

PP Dalvi, DR Edla, BR Purushothama - SN Computer Science, 2023 - Springer
Abstract The coronavirus disease (COVID-19) is a very contagious and dangerous disease
that affects the human respiratory system. Early detection of this disease is very crucial to …