Machine learning applications for COVID-19 outbreak management

A Heidari, N Jafari Navimipour, M Unal… - Neural Computing and …, 2022 - Springer
Recently, the COVID-19 epidemic has resulted in millions of deaths and has impacted
practically every area of human life. Several machine learning (ML) approaches are …

Reviewing methods of deep learning for diagnosing COVID-19, its variants and synergistic medicine combinations

Q Rafique, A Rehman, MS Afghan, HM Ahmad… - Computers in Biology …, 2023 - Elsevier
The COVID-19 pandemic has necessitated the development of reliable diagnostic methods
for accurately detecting the novel coronavirus and its variants. Deep learning (DL) …

Detection and classification of COVID-19 disease from X-ray images using convolutional neural networks and histogram of oriented gradients

AM Ayalew, AO Salau, BT Abeje, B Enyew - Biomedical Signal Processing …, 2022 - Elsevier
COVID-19 is now regarded as the most lethal disease caused by the novel coronavirus
disease of humans. The COVID-19 pandemic has spread to every country on the planet and …

Rethinking densely connected convolutional networks for diagnosing infectious diseases

P Podder, FB Alam, MRH Mondal, MJ Hasan, A Rohan… - Computers, 2023 - mdpi.com
Due to its high transmissibility, the COVID-19 pandemic has placed an unprecedented
burden on healthcare systems worldwide. X-ray imaging of the chest has emerged as a …

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 …

Detection of post-COVID-19-related pulmonary diseases in X-ray images using Vision Transformer-based neural network

A Mezina, R Burget - Biomedical Signal Processing and Control, 2024 - Elsevier
Objective: Computer methods related to the diagnosis of COVID-19 disease have
progressed significantly in recent years. Chest X-ray analysis supported by artificial …

Explainable COVID-19 detection based on chest x-rays using an end-to-end RegNet architecture

M Chetoui, MA Akhloufi, EM Bouattane, J Abdulnour… - Viruses, 2023 - mdpi.com
COVID-19, which is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-
CoV-2), is one of the worst pandemics in recent history. The identification of patients …

Predicting difficult airway intubation in thyroid surgery using multiple machine learning and deep learning algorithms

CM Zhou, Y Wang, Q Xue, JJ Yang, Y Zhu - Frontiers in public health, 2022 - frontiersin.org
Background In this paper, we examine whether machine learning and deep learning can be
used to predict difficult airway intubation in patients undergoing thyroid surgery. Methods We …

HCO-RLF: Hybrid classification optimization using recurrent learning and fuzzy for COVID-19 detection on CT images

K Balasamy, V Seethalakshmi - Biomedical Signal Processing and Control, 2025 - Elsevier
COVID-19 infection detection through initial lesion classification provides early diagnosis
and prevents breathing difficulties. Detecting the infectious part of the lungs using …

Peer-to-peer federated learning for COVID-19 detection using transformers

M Chetoui, MA Akhloufi - Computers, 2023 - mdpi.com
The simultaneous advances in deep learning and the Internet of Things (IoT) have benefited
distributed deep learning paradigms. Federated learning is one of the most promising …