Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Prognostic Value and Reproducibility of AI-assisted Analysis of Lung Involvement in COVID-19 at Low-Dose Submillisievert Chest CT: Sample Size Implications for Clinical Trials
22
Zitationen
17
Autoren
2020
Jahr
Abstract
AI-assisted analysis of lung involvement on submillisievert low-dose chest CT outperformed conventional visual analysis in predicting outcome in COVID-19 patients while reducing CT variability. Lung involvement on chest CT could be used as a reliable metric in future clinical trials.
Ähnliche Arbeiten
Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study
2020 · 22.618 Zit.
La certeza de lo impredecible: Cultura Educación y Sociedad en tiempos de COVID19
2020 · 19.271 Zit.
A Multi-Modal Distributed Real-Time IoT System for Urban Traffic Control (Invited Paper)
2024 · 14.266 Zit.
UNet++: A Nested U-Net Architecture for Medical Image Segmentation
2018 · 8.577 Zit.
Review of deep learning: concepts, CNN architectures, challenges, applications, future directions
2021 · 7.194 Zit.