Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Reliability and validity of an artificial intelligence-assisted system for the detection of abnormalities in chest and bone radiographs in an emergency department
0
Zitationen
25
Autoren
2025
Jahr
Abstract
The evaluated AI systems demonstrate clinically relevant performance in the emergency setting, significantly enhancing the diagnostic capacity of emergency physicians. Their high sensitivity for fracture detection and high NPV for pulmonary nodules, pneumothorax, and fractures establish them as a high-impact safety tool.
Ähnliche Arbeiten
Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study
2020 · 22.609 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 · 14.253 Zit.
UNet++: A Nested U-Net Architecture for Medical Image Segmentation
2018 · 8.498 Zit.
Review of deep learning: concepts, CNN architectures, challenges, applications, future directions
2021 · 7.114 Zit.
Autoren
- Raissa de Fátima Silva Afons
- Pilar Gallardo-Rodríguez
- Begoña Espinosa
- A. Bautista Hernández
- Javier Serrano
- Mónica Veguillas
- María Corell
- Raúl Garrido Chamorro
- J.J. Arenas-Jiménez
- C. Rodríguez
- Álvaro Abellón Fernández
- Álvaro Palazón Ruíz de Tremiño
- María Javiera Garfias Baladrón
- Víctor Arribas
- Pablo Chico-Sánchez
- Panagiota Valenti
- Maydelín Campos González
- Carlos Martínez Riera
- David Moliner Mateu
- José Tudela Serrano
- Emilio Vivancos Rubio
- Bernardo Valdivieso
- Luis Concepción
- José Sánchez–Payá
- Pere Llorens‐Soriano