Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Fostering a Healthy AI Ecosystem for Radiology: Conclusions of the 2018 RSNA Summit on AI in Radiology
20
Zitationen
4
Autoren
2019
Jahr
Abstract
The 2018 RSNA Summit on AI in Radiology brought together a diverse group of stakeholders to identify and prioritize areas of need related to artificial intelligence in radiology. This article presents the proceedings of the summit with emphasis on RSNA’s role in leading, organizing, and catalyzing change during this important time in radiology. Keywords: Impact of AI on education, Patient scheduling/no-show prediction, Resource allocation, Staffing © RSNA, 2019
Ähnliche Arbeiten
Refinement and reassessment of the SERVQUAL scale.
1991 · 3.967 Zit.
Radiobiology for the Radiologist.
1974 · 3.502 Zit.
ACR Thyroid Imaging, Reporting and Data System (TI-RADS): White Paper of the ACR TI-RADS Committee
2017 · 2.445 Zit.
Accuracy of Physician Self-assessment Compared With Observed Measures of Competence
2006 · 2.330 Zit.
Technology as an Occasion for Structuring: Evidence from Observations of CT Scanners and the Social Order of Radiology Departments
1986 · 2.257 Zit.