Understanding the pathophysiology of typical acute respiratory distress syndrome and severe COVID-19

L Ball, PL Silva, DR Giacobbe, M Bassetti… - Expert Review of …, 2022 - Taylor & Francis
Introduction Typical acute respiratory distress syndrome (ARDS) and severe coronavirus-19
(COVID-19) pneumonia share complex pathophysiology, a high mortality rate, and an unmet …

Covid-19 image data collection: Prospective predictions are the future

JP Cohen, P Morrison, L Dao, K Roth… - arXiv preprint arXiv …, 2020 - arxiv.org
Across the world's coronavirus disease 2019 (COVID-19) hot spots, the need to streamline
patient diagnosis and management has become more pressing than ever. As one of the …

Computational lung modelling in respiratory medicine

S Neelakantan, Y Xin, DP Gaver… - Journal of The …, 2022 - royalsocietypublishing.org
Computational modelling of the lungs is an active field of study that integrates computational
advances with lung biophysics, biomechanics, physiology and medical imaging to promote …

Deep neural network to detect COVID-19: one architecture for both CT Scans and Chest X-rays

H Mukherjee, S Ghosh, A Dhar, SM Obaidullah… - Applied …, 2021 - Springer
Since December 2019, the novel COVID-19's spread rate is exponential, and AI-driven tools
are used to prevent further spreading [1]. They can help predict, screen, and diagnose …

Close down the lungs and keep them resting to minimize ventilator-induced lung injury

P Pelosi, PRM Rocco, M Gama de Abreu - Critical Care, 2018 - Springer
This article is one of ten reviews selected from the Annual Update in Intensive Care and
Emergency Medicine 2018. Other selected articles can be found online at https://www …

Lung distribution of gas and blood volume in critically ill COVID-19 patients: a quantitative dual-energy computed tomography study

L Ball, C Robba, J Herrmann, SE Gerard, Y Xin… - Critical Care, 2021 - Springer
Background Critically ill COVID-19 patients have pathophysiological lung features
characterized by perfusion abnormalities. However, to date no study has evaluated whether …

A survey on deep learning in COVID-19 diagnosis

X Han, Z Hu, S Wang, Y Zhang - Journal of imaging, 2022 - mdpi.com
According to the World Health Organization statistics, as of 25 October 2022, there have
been 625,248,843 confirmed cases of COVID-19, including 65,622,281 deaths worldwide …

A methodical exploration of imaging modalities from dataset to detection through machine learning paradigms in prominent lung disease diagnosis: a review

S Kumar, H Kumar, G Kumar, SP Singh, A Bijalwan… - BMC Medical …, 2024 - Springer
Background Lung diseases, both infectious and non-infectious, are the most prevalent
cause of mortality overall in the world. Medical research has identified pneumonia, lung …

In-vivo lung fibrosis staging in a bleomycin-mouse model: a new micro-CT guided densitometric approach

L Mecozzi, M Mambrini, F Ruscitti, E Ferrini… - Scientific reports, 2020 - nature.com
Although increasing used in the preclinical testing of new anti-fibrotic drugs, a thorough
validation of micro-computed tomography (CT) in pulmonary fibrosis models has not been …

Electrical Impedance Tomography Guided by Digital Twins and Deep Learning for Lung Monitoring

L Zhu, W Lu, M Soleimani, Z Li… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
In recent years, there has been an increasing interest in applying electrical impedance
tomography (EIT) in lung monitoring due to its advantages of being noninvasive …