Review on the evaluation and development of artificial intelligence for COVID-19 containment
Artificial intelligence has significantly enhanced the research paradigm and spectrum with a
substantiated promise of continuous applicability in the real world domain. Artificial …
substantiated promise of continuous applicability in the real world domain. Artificial …
Viral outbreaks detection and surveillance using wastewater-based epidemiology, viral air sampling, and machine learning techniques: A comprehensive review and …
A viral outbreak is a global challenge that affects public health and safety. The coronavirus
disease 2019 (COVID-19) has been spreading globally, affecting millions of people …
disease 2019 (COVID-19) has been spreading globally, affecting millions of people …
Explainable machine learning models based on multimodal time-series data for the early detection of Parkinson's disease
Background and objectives Parkinson's Disease (PD) is a devastating chronic neurological
condition. Machine learning (ML) techniques have been used in the early prediction of PD …
condition. Machine learning (ML) techniques have been used in the early prediction of PD …
[HTML][HTML] Towards using cough for respiratory disease diagnosis by leveraging Artificial Intelligence: A survey
Cough acoustics contain multitudes of vital information about pathomorphological
alterations in the respiratory system. Reliable and accurate detection of cough events by …
alterations in the respiratory system. Reliable and accurate detection of cough events by …
Chest X-ray Images for Lung Disease Detection Using Deep Learning Techniques: A Comprehensive Survey
MAA Al-qaness, J Zhu, D AL-Alimi, A Dahou… - … Methods in Engineering, 2024 - Springer
In medical imaging, the last decade has witnessed a remarkable increase in the availability
and diversity of chest X-ray (CXR) datasets. Concurrently, there has been a significant …
and diversity of chest X-ray (CXR) datasets. Concurrently, there has been a significant …
A comprehensive review of machine learning used to combat COVID-19
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 …
start of the pandemic in 2019. As of June 2022, over 539 million cases have been confirmed …
Novel coronavirus and common pneumonia detection from CT scans using deep learning-based extracted features
COVID-19 which was announced as a pandemic on 11 March 2020, is still infecting millions
to date as the vaccines that have been developed do not prevent the disease but rather …
to date as the vaccines that have been developed do not prevent the disease but rather …
An efficient edge/cloud medical system for rapid detection of level of consciousness in emergency medicine based on explainable machine learning models
Emergency medicine (EM) is one of the attractive research fields in which researchers
investigate their efforts to diagnose and treat unforeseen illnesses or injuries. There are …
investigate their efforts to diagnose and treat unforeseen illnesses or injuries. There are …
Recommender system for the efficient treatment of COVID-19 using a convolutional neural network model and image similarity
Background: Hospitals face a significant problem meeting patients' medical needs during
epidemics, especially when the number of patients increases rapidly, as seen during the …
epidemics, especially when the number of patients increases rapidly, as seen during the …
On the adoption of modern technologies to fight the COVID-19 pandemic: a technical synthesis of latest developments
A Majeed, X Zhang - COVID, 2023 - mdpi.com
In the ongoing COVID-19 pandemic, digital technologies have played a vital role to minimize
the spread of COVID-19, and to control its pitfalls for the general public. Without such …
the spread of COVID-19, and to control its pitfalls for the general public. Without such …