A comprehensive review of machine learning used to combat COVID-19

R Gomes, C Kamrowski, J Langlois, P Rozario, I Dircks… - Diagnostics, 2022 - mdpi.com
Coronavirus disease (COVID-19) has had a significant impact on global health since the
start of the pandemic in 2019. As of June 2022, over 539 million cases have been confirmed …

Smart healthcare: A prospective future medical approach for COVID-19

DM Yang, TJ Chang, KF Hung, ML Wang… - Journal of the …, 2023 - journals.lww.com
COVID-19 has greatly affected human life for over 3 years. In this review, we focus on smart
healthcare solutions that address major requirements for coping with the COVID-19 …

PETLFC: Parallel ensemble transfer learning based framework for COVID-19 differentiation and prediction using deep convolutional neural network models

P Misra, N Panigrahi, S Gopal Krishna Patro… - Multimedia Tools and …, 2024 - Springer
Despite a worldwide research involvement in the global COVID-19 pandemic, the research
community is still struggling to develop reliable and faster prediction mechanisms for this …

[HTML][HTML] A multi-modal bone suppression, lung segmentation, and classification approach for accurate COVID-19 detection using chest radiographs

G Rani, A Misra, VS Dhaka, D Buddhi… - Intelligent Systems with …, 2022 - Elsevier
The high transmission rate of COVID-19 and the lack of quick, robust, and intelligent systems
for its detection have become a point of concern for the public, Government, and health …

ETSVF-COVID19: efficient two-stage voting framework for COVID-19 detection

K Akyol - Neural Computing and Applications, 2024 - Springer
COVID-19 disease, an outbreak in the spring of 2020, reached very alarming dimensions for
humankind due to many infected patients during the pandemic and the heavy workload of …

Internet of medical things in the COVID-19 Era: a systematic literature review

A Hemmati, AM Rahmani - Sustainability, 2022 - mdpi.com
In recent years, the medical industry has rapidly modernized, incorporating technology to aid
in accelerating and simplifying procedures for better accuracy. This technology is becoming …

Multi-condition controlled sedimentary facies modeling based on generative adversarial network

F Hu, C Wu, J Shang, Y Yan, L Wang… - Computers & Geosciences, 2023 - Elsevier
Obtaining reliable sedimentary facies models is critical for geology, which primarily involves
inferring conditional distributions from sparse wells. Multiple-point simulation (MPS) …

Glaucoma detection with explainable AI using convolutional neural networks based feature extraction and machine learning classifiers

VK Velpula, D Sharma, LD Sharma, A Roy… - IET Image …, 2024 - Wiley Online Library
Glaucoma is an eye disease that damages the optic nerve as a result of vision loss, it is the
leading cause of blindness worldwide. Due to the time‐consuming, inaccurate, and manual …

Optimized transfer learning based dementia prediction system for rehabilitation therapy planning

PH Kuo, CT Huang, TC Yao - IEEE Transactions on Neural …, 2023 - ieeexplore.ieee.org
Dementia is a neurodegenerative disease that causes a progressive deterioration of
thinking, memory, and the ability to perform daily tasks. Other common symptoms include …

A Hybrid Deep Fused Learning Approach to Segregate Infectious Diseases.

J Rasheed, S Alsubai - Computers, Materials & Continua, 2023 - search.ebscohost.com
Humankind is facing another deadliest pandemic of all times in history, caused by COVID-
19. Apart from this challenging pandemic, World Health Organization (WHO) considers …