Five new limonoids, tabularisins E-I ( 1- 5), and a new dinorcycloartane, (24 R)-28,29-dinor-cycloartane-3beta,24,25-triol ( 6), together with three known compounds, were isolated from the twigs and leaves of Chukrasia tabularis var. velutina. Their structures were elucidated primarily on the basis of spectroscopic methods.
Objectives An artificial intelligence model was adopted to identify mild COVID-19 pneumonia from computed tomography (CT) volumes, and its diagnostic performance was then evaluated. Methods In this retrospective multicenter study, an atrous convolution-based deep learning model was established for the computer-assisted diagnosis of mild COVID-19 pneumonia. The dataset included 2087 chest CT exams collected from four hospitals between 1 January 2019 and 31 May 2020. The true positive rate, true negative rate, receiver operating characteristic curve, area under the curve (AUC) and convolutional feature map were used to evaluate the model. Results The proposed deep learning model was trained on 1538 patients and tested on an independent testing cohort of 549 patients. The overall sensitivity was 91.5% (195/213; p < 0.001, 95% CI: 89.2-93.9%), the overall specificity was 90.5% (304/ 336; p < 0.001, 95% CI: 88.0-92.9%) and the general AUC value was 0.955 (p < 0.001). Conclusions A deep learning model can accurately detect COVID-19 and serve as an important supplement to the COVID-19 reverse transcription-polymerase chain reaction (RT-PCR) test. Key Points • The implementation of a deep learning model to identify mild COVID-19 pneumonia was confirmed to be effective and feasible. • The strategy of using a binary code instead of the region of interest label to identify mild COVID-19 pneumonia was verified. • This AI model can assist in the early screening of COVID-19 without interfering with normal clinical examinations. Keywords Computer-assisted diagnosis. Volume CT. COVID-19. Artificial intelligence. Deep learning Abbreviations AUC Area under the curve CAD Computer-assisted diagnosis CAP Community-acquired pneumonia COVID-19 Coronavirus disease 2019 IgG Immunoglobulin G IgM Immunoglobulin M ROC Receiver operating characteristic RT-PCR Reverse transcription-polymerase chain reaction SSAC Sparse separable atrous convolution Jin-Cao Yao and Tao Wang contributed equally to this work.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.