Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Use of Artificial Intelligence in Nononcologic Interventional Radiology: Current State and Future Directions
9
Zitationen
5
Autoren
2021
Jahr
Abstract
The future of radiology is disproportionately linked to the applications of artificial intelligence (AI). Recent exponential advancements in AI are already beginning to augment the clinical practice of radiology. Driven by a paucity of review articles in the area, this article aims to discuss applications of AI in non-oncologic IR across procedural planning, execution, and follow-up along with a discussion on the future directions of the field. Applications in vascular imaging, radiomics, touchless software interactions, robotics, natural language processing, post-procedural outcome prediction, device navigation, and image acquisition are included. Familiarity with AI study analysis will help open the current 'black box' of AI research and help bridge the gap between the research laboratory and clinical practice.
Ähnliche Arbeiten
New response evaluation criteria in solid tumours: Revised RECIST guideline (version 1.1)
2008 · 28.943 Zit.
TNM Classification of Malignant Tumours
1987 · 16.123 Zit.
A survey on deep learning in medical image analysis
2017 · 13.625 Zit.
Reduced Lung-Cancer Mortality with Low-Dose Computed Tomographic Screening
2011 · 10.776 Zit.
The American Joint Committee on Cancer: the 7th Edition of the AJCC Cancer Staging Manual and the Future of TNM
2010 · 9.111 Zit.