Artificial intelligence and COVID-19 using chest CT scan and chest X-ray images: machine learning and deep learning approaches for diagnosis and treatment
Objective: To report an overview and update on Artificial Intelligence (AI) and COVID-19
using chest Computed Tomography (CT) scan and chest X-ray images (CXR). Machine …
using chest Computed Tomography (CT) scan and chest X-ray images (CXR). Machine …
Real-world evidence—current developments and perspectives
F Schad, A Thronicke - … journal of environmental research and public …, 2022 - mdpi.com
Real-world evidence (RWE) is increasingly involved in the early benefit assessment of
medicinal drugs. It is expected that RWE will help to speed up approval processes …
medicinal drugs. It is expected that RWE will help to speed up approval processes …
Diagnostic approaches for COVID-19: lessons learned and the path forward
Coronavirus disease 2019 (COVID-19) is a transmitted respiratory disease caused by the
infection of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Although …
infection of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Although …
Novel comparative study for the detection of COVID-19 using CT scan and chest X-ray images
The number of coronavirus disease (COVID-19) cases is constantly rising as the pandemic
continues, with new variants constantly emerging. Therefore, to prevent the virus from …
continues, with new variants constantly emerging. Therefore, to prevent the virus from …
The revolution of lateral flow assay in the field of AMR detection
H Boutal, C Moguet, L Pommiès, S Simon, T Naas… - Diagnostics, 2022 - mdpi.com
The global spread of antimicrobial resistant (AMR) bacteria represents a considerable public
health concern, yet their detection and identification of their resistance mechanisms remain …
health concern, yet their detection and identification of their resistance mechanisms remain …
Diagnostic accuracy of three commercially available one step RT-PCR assays for the detection of SARS-CoV-2 in resource limited settings
A Sisay, A Abera, B Dufera, T Endrias, G Tasew… - PloS one, 2022 - journals.plos.org
Background COVID-19 is an ongoing public health pandemic regardless of the countless
efforts made by various actors. Quality diagnostic tests are important for early detection and …
efforts made by various actors. Quality diagnostic tests are important for early detection and …
[HTML][HTML] Application and utility of boosting machine learning model based on laboratory test in the differential diagnosis of non-COVID-19 pneumonia and COVID-19
SM Baik, KS Hong, DJ Park - Clinical Biochemistry, 2023 - Elsevier
Abstract Background Non-Coronavirus disease 2019 (COVID-19) pneumonia and COVID-
19 have similar clinical features but last for different periods, and consequently, require …
19 have similar clinical features but last for different periods, and consequently, require …
Estimating the sensitivity and specificity of serum ELISA and pooled and individual fecal PCR for detecting Mycobacterium avium subspecies paratuberculosis in …
P Johnson, L McLeod, J Campbell… - Frontiers in Veterinary …, 2022 - frontiersin.org
While Johne's disease (JD) is less common in beef than in dairy herds, consolidation is
increasing transmission risk. Estimates of Mycobacterium avium spp. paratuberculosis …
increasing transmission risk. Estimates of Mycobacterium avium spp. paratuberculosis …
Comparison of test-negative and syndrome-negative controls in SARS-CoV-2 vaccine effectiveness evaluations for preventing COVID-19 hospitalizations in the …
C Turbyfill, K Adams, MW Tenforde, NL Murray… - Vaccine, 2022 - Elsevier
Background Test-negative design (TND) studies have produced validated estimates of
vaccine effectiveness (VE) for influenza vaccine studies. However, syndrome-negative …
vaccine effectiveness (VE) for influenza vaccine studies. However, syndrome-negative …
Estimating cutoff values for diagnostic tests to achieve target specificity using extreme value theory
Background Rapidly developing tests for emerging diseases is critical for early disease
monitoring. In the early stages of an epidemic, when low prevalences are expected, high …
monitoring. In the early stages of an epidemic, when low prevalences are expected, high …