Deep learning in the detection and diagnosis of COVID‐19 using radiology modalities: a systematic review

M Ghaderzadeh, F Asadi - Journal of healthcare engineering, 2021 - Wiley Online Library
Introduction. The early detection and diagnosis of COVID‐19 and the accurate separation of
non‐COVID‐19 cases at the lowest cost and in the early stages of the disease are among …

[HTML][HTML] Artificial intelligence: A critical review of applications for lung nodule and lung cancer

C de Margerie-Mellon, G Chassagnon - Diagnostic and Interventional …, 2023 - Elsevier
Artificial intelligence (AI) is a broad concept that usually refers to computer programs that
can learn from data and perform certain specific tasks. In the recent years, the growth of …

[HTML][HTML] COVID-19-the role of artificial intelligence, machine learning, and deep learning: a newfangled

DN Vinod, SRS Prabaharan - Archives of Computational Methods in …, 2023 - Springer
The absolute previously infected novel coronavirus (COVID-19) was found in Wuhan, China,
in December 2019. The COVID-19 epidemic has spread to more than 220 nations and …

[HTML][HTML] The acute and chronic implications of the COVID-19 virus on the cardiovascular system in adults: A systematic review

RE Ashton, BE Philips, M Faghy - Progress in Cardiovascular Diseases, 2023 - Elsevier
Abstract Despite coronavirus disease 2019 (COVID-19) primarily being identified as a
respiratory illness, some patients who seemingly recovered from initial infection, developed …

[HTML][HTML] COVID-19 diagnosis from chest x-rays: developing a simple, fast, and accurate neural network

V Nikolaou, S Massaro, M Fakhimi… - … information science and …, 2021 - Springer
Purpose Chest x-rays are a fast and inexpensive test that may potentially diagnose COVID-
19, the disease caused by the novel coronavirus. However, chest imaging is not a first-line …

[HTML][HTML] An intelligent sensor based decision support system for diagnosing pulmonary ailment through standardized chest x-ray scans

S Batra, H Sharma, W Boulila, V Arya, P Srivastava… - Sensors, 2022 - mdpi.com
Academics and the health community are paying much attention to developing smart remote
patient monitoring, sensors, and healthcare technology. For the analysis of medical scans …

[HTML][HTML] A deep batch normalized convolution approach for improving COVID-19 detection from chest X-ray images

I Al-Shourbaji, PH Kachare, L Abualigah, ME Abdelhag… - Pathogens, 2022 - mdpi.com
Pre-trained machine learning models have recently been widely used to detect COVID-19
automatically from X-ray images. Although these models can selectively retrain their layers …

Management of covid-19 detection using artificial intelligence in 2020 pandemic

M Ghaderzadeh, M Aria - … of the 5th international conference on medical …, 2021 - dl.acm.org
Successful early detection of Covid-19 disease plays an important role in improving the
effectiveness of treatment and managing the pandemic. Various diagnostic methods for the …

[HTML][HTML] A deep learning-based application for COVID-19 diagnosis on CT: the imaging COVID-19 AI initiative

L Topff, J Sánchez-García, R López-González… - Plos one, 2023 - journals.plos.org
Background Recently, artificial intelligence (AI)-based applications for chest imaging have
emerged as potential tools to assist clinicians in the diagnosis and management of patients …

[HTML][HTML] Ultra-low-dose chest CT performance for the detection of viral pneumonia patterns during the COVID-19 outbreak period: a monocentric experience

J Greffier, A Hoballah, A Sadate… - … Imaging in Medicine …, 2021 - ncbi.nlm.nih.gov
Background Ultra low dose chest computed tomography (CT) acquisitions have been used
for selected emergency room patients with acute dyspnea or minor thoracic trauma. The …