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Accepted for/Published in: Interactive Journal of Medical Research

Date Submitted: Apr 11, 2022
Open Peer Review Period: Apr 11, 2022 - May 26, 2022
Date Accepted: Sep 13, 2022
(closed for review but you can still tweet)

The final, peer-reviewed published version of this preprint can be found here:

Levels of Autonomous Radiology

Ghuwalewala S, Kulkarni V, Pant R, Kharat A

Levels of Autonomous Radiology

Interact J Med Res 2022;11(2):e38655

DOI: 10.2196/38655

PMID: 36476422

PMCID: 9773033

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

Levels of Autonomous Radiology

  • Suraj Ghuwalewala; 
  • Viraj Kulkarni; 
  • Richa Pant; 
  • Amit Kharat

ABSTRACT

Radiology, being one of the younger disciplines of medicine with a history of just over a century, has witnessed tremendous technological advancements and has revolutionized the way we practice medicine today. In the last few decades, medical imaging modalities have generated seismic amounts of medical data. The development and adoption of Artificial Intelligence (AI) applications using this data will lead to the next phase of evolution in radiology. It will include automating laborious manual tasks such as annotations, report-generation, etc., along with the initial radiological assessment of cases to aid radiologists in their evaluation workflow. We propose a level-wise classification for the progression of automation in radiology, explaining AI assistance at each level with corresponding challenges and solutions. We hope that such discussions can help us address challenges in a structured way and take the necessary steps to ensure the smooth adoption of new technologies in radiology.


 Citation

Please cite as:

Ghuwalewala S, Kulkarni V, Pant R, Kharat A

Levels of Autonomous Radiology

Interact J Med Res 2022;11(2):e38655

DOI: 10.2196/38655

PMID: 36476422

PMCID: 9773033

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