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. 2021;5(4):331-337.
doi: 10.1055/s-0041-1726300. Epub 2021 Jul 17.

Use of Artificial Intelligence in Non-Oncologic Interventional Radiology: Current State and Future Directions

Rohil Malpani  1 , Christopher W Petty  1 , Neha Bhatt  1 , Lawrence H Staib  1 , Julius Chapiro  1
Affiliations

Use of Artificial Intelligence in Non-Oncologic Interventional Radiology: Current State and Future Directions

Rohil Malpani et al. Dig Dis Interv. 2021.

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.

Keywords: artificial intelligence; deep learning; interventional radiology; machine learning; radiomics.

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Figures

Figure 1:
Figure 1:
Schematic Showing the different Applications of Artificial Intelligence in Non-Oncologic Interventional Radiology Based on the literature, different aspects of the applications of artificial intelligence in non-oncologic interventional radiology were identified and illustrated schematically using a Circle-Spoke diagram
See this image and copyright information in PMC

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