Automated detection and forecasting of covid-19 using deep learning techniques: A review
Abstract In March 2020, the World Health Organization (WHO) declared COVID-19 a global
epidemic, caused by the SARS-CoV-2 virus. Initially, COVID-19 was diagnosed using real …
epidemic, caused by the SARS-CoV-2 virus. Initially, COVID-19 was diagnosed using real …
Review of machine learning in lung ultrasound in COVID-19 pandemic
Ultrasound imaging of the lung has played an important role in managing patients with
COVID-19–associated pneumonia and acute respiratory distress syndrome (ARDS). During …
COVID-19–associated pneumonia and acute respiratory distress syndrome (ARDS). During …
A lightweight CNN-based network on COVID-19 detection using X-ray and CT images
ML Huang, YC Liao - Computers in Biology and Medicine, 2022 - Elsevier
Background and objectives The traditional method of detecting COVID-19 disease mainly
rely on the interpretation of computer tomography (CT) or X-ray images (X-ray) by doctors or …
rely on the interpretation of computer tomography (CT) or X-ray images (X-ray) by doctors or …
State of the art in lung ultrasound, shifting from qualitative to quantitative analyses
Lung ultrasound (LUS) has been increasingly expanding since the 1990s, when the clinical
relevance of vertical artifacts was first reported. However, the massive spread of LUS is only …
relevance of vertical artifacts was first reported. However, the massive spread of LUS is only …
[HTML][HTML] Fluent: Transformer for detecting lung consolidations in videos using fused lung ultrasound encodings
Pneumonia is the leading cause of death among children around the world. According to
WHO, a total of 740,180 lives under the age of five were lost due to pneumonia in 2019 …
WHO, a total of 740,180 lives under the age of five were lost due to pneumonia in 2019 …
Lung Ultrasound Reduces Chest X-rays in Postoperative Care after Thoracic Surgery: Is There a Role for Artificial Intelligence?—Systematic Review
M Malik, A Dzian, M Števík, Š Vetešková, A Al Hakim… - Diagnostics, 2023 - mdpi.com
Background: Chest X-ray (CXR) remains the standard imaging modality in postoperative
care after non-cardiac thoracic surgery. Lung ultrasound (LUS) showed promising results in …
care after non-cardiac thoracic surgery. Lung ultrasound (LUS) showed promising results in …
Breathe out the secret of the lung: video classification of exhaled flows from normal and asthmatic lung models using CNN-Long Short-Term Memory networks
In this study, we present a novel approach to differentiate normal and diseased lungs based
on exhaled flows from 3D-printed lung models simulating normal and asthmatic conditions …
on exhaled flows from 3D-printed lung models simulating normal and asthmatic conditions …
Automatic deep learning-based consolidation/collapse classification in lung ultrasound images for COVID-19 induced pneumonia
N Durrani, D Vukovic, J van der Burgt, M Antico… - Scientific Reports, 2022 - nature.com
Our automated deep learning-based approach identifies consolidation/collapse in LUS
images to aid in the identification of late stages of COVID-19 induced pneumonia, where …
images to aid in the identification of late stages of COVID-19 induced pneumonia, where …
MobilePTX: sparse coding for pneumothorax detection given limited training examples
Abstract Point-of-Care Ultrasound (POCUS) refers to clinician-performed and interpreted
ultrasonography at the patient's bedside. Interpreting these images requires a high level of …
ultrasonography at the patient's bedside. Interpreting these images requires a high level of …
Ultrasound imaging of lung disease and its relationship to histopathology: An experimentally validated simulation approach
Lung ultrasound (LUS) is a widely used technique in clinical lung assessment, yet the
relationship between LUS images and the underlying disease remains poorly understood …
relationship between LUS images and the underlying disease remains poorly understood …