Artificial intelligence-driven assessment of radiological images for COVID-19

Y Bouchareb, PM Khaniabadi, F Al Kindi… - Computers in biology …, 2021 - Elsevier
Artificial Intelligence (AI) methods have significant potential for diagnosis and prognosis of
COVID-19 infections. Rapid identification of COVID-19 and its severity in individual patients …

A hybrid machine learning/deep learning COVID-19 severity predictive model from CT images and clinical data

M Chieregato, F Frangiamore, M Morassi, C Baresi… - Scientific reports, 2022 - nature.com
COVID-19 clinical presentation and prognosis are highly variable, ranging from
asymptomatic and paucisymptomatic cases to acute respiratory distress syndrome and multi …

Diagnosis/prognosis of covid-19 chest images via machine learning and hypersignal processing: Challenges, opportunities, and applications

A Mohammadi, Y Wang, N Enshaei… - IEEE Signal …, 2021 - ieeexplore.ieee.org
The novel coronavirus disease, COVID-19, has rapidly and abruptly changed the world as
we knew it in 2020. It has become the most unprecedented challenge to analytic …

[HTML][HTML] Development and validation of a machine learning approach for automated severity assessment of COVID-19 based on clinical and imaging data …

JC Quiroz, YZ Feng, ZY Cheng… - JMIR Medical …, 2021 - medinform.jmir.org
Background: COVID-19 has overwhelmed health systems worldwide. It is important to
identify severe cases as early as possible, such that resources can be mobilized and …

CT-based severity assessment for COVID-19 using weakly supervised non-local CNN

R Karthik, R Menaka, M Hariharan, D Won - Applied Soft Computing, 2022 - Elsevier
Evaluating patient criticality is the foremost step in administering appropriate COVID-19
treatment protocols. Learning an Artificial Intelligence (AI) model from clinical data for …

[HTML][HTML] Enriching Data Science and Health Care Education: Application and Impact of Synthetic Data Sets Through the Health Gym Project

I Nicholas, H Kuo, O Perez-Concha, M Hanly… - JMIR Medical …, 2024 - mededu.jmir.org
Large-scale medical data sets are vital for hands-on education in health data science but
are often inaccessible due to privacy concerns. Addressing this gap, we developed the …

A state-of-the-art survey on artificial intelligence to fight COVID-19

MM Islam, TN Poly, B Alsinglawi, MC Lin… - Journal of clinical …, 2021 - mdpi.com
Artificial intelligence (AI) has shown immense potential to fight COVID-19 in many ways. This
paper focuses primarily on AI's role in managing COVID-19 using digital images, clinical and …

Boosting covid-19 severity detection with infection-aware contrastive mixup classification

J Hou, J Xu, N Zhang, Y Zhang, X Zhang… - European Conference on …, 2022 - Springer
This paper presents our solution for the 2nd COVID-19 Severity Detection Competition. This
task aims to distinguish the Mild, Moderate, Severe, and Critical grades in COVID-19 chest …

[HTML][HTML] Deep learning methodology for differentiating glioma recurrence from radiation necrosis using multimodal magnetic resonance imaging: algorithm …

Y Gao, X Xiao, B Han, G Li, X Ning… - JMIR medical …, 2020 - medinform.jmir.org
Background: The radiological differential diagnosis between tumor recurrence and radiation-
induced necrosis (ie, pseudoprogression) is of paramount importance in the management of …

Determination of the severity and percentage of COVID-19 infection through a hierarchical deep learning system

S Ortiz, F Rojas, O Valenzuela, LJ Herrera… - Journal of Personalized …, 2022 - mdpi.com
The coronavirus disease 2019 (COVID-19) has caused millions of deaths and one of the
greatest health crises of all time. In this disease, one of the most important aspects is the …