[HTML][HTML] Deep learning for chest X-ray analysis: A survey

E Çallı, E Sogancioglu, B van Ginneken… - Medical Image …, 2021 - Elsevier
Recent advances in deep learning have led to a promising performance in many medical
image analysis tasks. As the most commonly performed radiological exam, chest …

Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans

M Roberts, D Driggs, M Thorpe, J Gilbey… - Nature Machine …, 2021 - nature.com
Abstract Machine learning methods offer great promise for fast and accurate detection and
prognostication of coronavirus disease 2019 (COVID-19) from standard-of-care chest …

AI for radiographic COVID-19 detection selects shortcuts over signal

AJ DeGrave, JD Janizek, SI Lee - Nature Machine Intelligence, 2021 - nature.com
Artificial intelligence (AI) researchers and radiologists have recently reported AI systems that
accurately detect COVID-19 in chest radiographs. However, the robustness of these systems …

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 …

Assessing the trustworthiness of saliency maps for localizing abnormalities in medical imaging

N Arun, N Gaw, P Singh, K Chang… - Radiology: Artificial …, 2021 - pubs.rsna.org
Purpose To evaluate the trustworthiness of saliency maps for abnormality localization in
medical imaging. Materials and Methods Using two large publicly available radiology …

Applications of artificial intelligence in battling against covid-19: A literature review

M Tayarani - Chaos, Solitons and Fractals, 2020 - researchprofiles.herts.ac.uk
Colloquially known as coronavirus, the Severe Acute Respiratory Syndrome CoronaVirus 2
(SARS-CoV-2), that causes CoronaVirus Disease 2019 (COVID-19), has become a matter of …

COVID-19 imaging: what we know now and what remains unknown

JP Kanne, H Bai, A Bernheim, M Chung, LB Haramati… - Radiology, 2021 - pubs.rsna.org
Infection with SARS-CoV-2 ranges from an asymptomatic condition to a severe and
sometimes fatal disease, with mortality most frequently being the result of acute lung injury …

Current and emerging knowledge in COVID-19

YJ Jeong, YM Wi, H Park, JE Lee, SH Kim, KS Lee - Radiology, 2023 - pubs.rsna.org
COVID-19 has emerged as a pandemic leading to a global public health crisis of
unprecedented morbidity. A comprehensive insight into the imaging of COVID-19 has …

[HTML][HTML] Role of machine learning techniques to tackle the COVID-19 crisis: systematic review

HB Syeda, M Syed, KW Sexton, S Syed… - JMIR medical …, 2021 - medinform.jmir.org
Background: SARS-CoV-2, the novel coronavirus responsible for COVID-19, has caused
havoc worldwide, with patients presenting a spectrum of complications that have pushed …

AI-driven quantification, staging and outcome prediction of COVID-19 pneumonia

G Chassagnon, M Vakalopoulou, E Battistella… - Medical image …, 2021 - Elsevier
Abstract Coronavirus disease 2019 (COVID-19) emerged in 2019 and disseminated around
the world rapidly. Computed tomography (CT) imaging has been proven to be an important …