Role of artificial intelligence in COVID-19 detection

A Gudigar, U Raghavendra, S Nayak, CP Ooi… - Sensors, 2021 - mdpi.com
The global pandemic of coronavirus disease (COVID-19) has caused millions of deaths and
affected the livelihood of many more people. Early and rapid detection of COVID-19 is a …

The application of a deep learning system developed to reduce the time for RT-PCR in COVID-19 detection

Y Lee, YS Kim, D Lee, S Jeong, GH Kang, YS Jang… - Scientific reports, 2022 - nature.com
Reducing the time to diagnose COVID-19 helps to manage insufficient isolation-bed
resources and adequately accommodate critically ill patients. There is currently no …

Automated COVID-19 diagnosis and prognosis with medical imaging and who is publishing: a systematic review

AG Gillman, F Lunardo, J Prinable, G Belous… - … engineering sciences in …, 2021 - Springer
Objectives: To conduct a systematic survey of published techniques for automated diagnosis
and prognosis of COVID-19 diseases using medical imaging, assessing the validity of …

Radiomics-based machine learning differentiates “ground-glass” opacities due to COVID-19 from acute non-COVID-19 lung disease

A Delli Pizzi, AM Chiarelli, P Chiacchiaretta… - Scientific reports, 2021 - nature.com
Ground-glass opacities (GGOs) are a non-specific high-resolution computed tomography
(HRCT) finding tipically observed in early Coronavirus disesase 19 (COVID-19) pneumonia …

Chest CT texture-based radiomics analysis in differentiating COVID-19 from other interstitial pneumonia

D Caruso, F Pucciarelli, M Zerunian, B Ganeshan… - La radiologia …, 2021 - Springer
Purpose To evaluate the potential role of texture-based radiomics analysis in differentiating
Coronavirus Disease-19 (COVID-19) pneumonia from pneumonia of other etiology on Chest …

[HTML][HTML] IgG N-glycosylation cardiovascular age tracks cardiovascular risk beyond calendar age

Z Wu, Z Guo, Y Zheng, Y Wang, H Zhang, H Pan, Z Li… - Engineering, 2023 - Elsevier
The use of an altered immunoglobulin G (IgG) N-glycan pattern as an inflammation metric
has been reported in subclinical atherosclerosis and metabolic disorders, both of which are …

A transfer learning-based deep learning approach for automated Covid-19diagnosis with audio data

D Akgün, AT KABAKUŞ, ZK ŞENTÜRK… - Turkish Journal of …, 2021 - journals.tubitak.gov.tr
The COVID-19 pandemic has caused millions of deaths and changed daily life globally.
Countries have declared a half or full lockdown to prevent the spread of COVID-19 …

[HTML][HTML] An externally validated fully automated deep learning algorithm to classify COVID-19 and other pneumonias on chest computed tomography

A Vaidyanathan, J Guiot, F Zerka… - ERJ Open …, 2022 - Eur Respiratory Soc
Purpose In this study, we propose an artificial intelligence (AI) framework based on three-
dimensional convolutional neural networks to classify computed tomography (CT) scans of …

Klasifikasi Kasus COVID-19 dan SARS Berbasis Ciri Tekstur Menggunakan Metode Multi-Layer Perceptron

JF Azzahra, H Sumarti, HH Kusuma - Jurnal Fisika, 2022 - journal.unnes.ac.id
Abstract Corona Virus Disease 2019 (COVID-19) merupakan penyakit infeksi akut yang
disebabkan oleh virus corona sebagai sindrom pernafasan akut parah. SARS (Severe Acute …

[HTML][HTML] Development and External Validation of Clinical Features-based Machine Learning Models for Predicting COVID-19 in the Emergency Department

J Tay, YH Yen, K Rivera, EH Chou… - Western Journal of …, 2024 - ncbi.nlm.nih.gov
Methods To create our training/validation cohort (model development) we collected data
retrospectively from suspected COVID-19 patients at a US ED from February 23–May 12 …