Literature DB >> 33010212

Artificial Intelligence: A Private Practice Perspective.

Nina Kottler1.   

Abstract

Artificial intelligence (AI) is an exciting technology that can transform the practice of radiology. However, radiology AI is still immature with limited adopters, dominated by academic institutions, and few use cases in general practice. With scale and a focus on innovation, our practice has had the opportunity to be an early adopter of AI technology. We have gained experience identifying use cases that provide value for our patients and practice; selecting AI products and vendors; piloting vendors' AI algorithms; creating our own AI algorithms; implementing, optimizing, and maintaining these algorithms; garnering radiologist acceptance of these tools; and integrating AI into our radiologists' daily workflow. With this experience, our practice has both managed challenges and identified unexpected benefits of AI. To ensure a successful and scalable AI implementation, multiple steps are required, including preparing the data, systems, and radiologists. This article reviews our experience with AI and describes why each step is important.
Copyright © 2020 American College of Radiology. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Artificial intelligence; data strategy and governance; peer learning; physician engagement; workflow

Mesh:

Year:  2020        PMID: 33010212     DOI: 10.1016/j.jacr.2020.09.029

Source DB:  PubMed          Journal:  J Am Coll Radiol        ISSN: 1546-1440            Impact factor:   5.532


  3 in total

1.  Learning rate of students detecting and annotating pediatric wrist fractures in supervised artificial intelligence dataset preparations.

Authors:  Eszter Nagy; Robert Marterer; Franko Hržić; Erich Sorantin; Sebastian Tschauner
Journal:  PLoS One       Date:  2022-10-20       Impact factor: 3.752

Review 2.  [Artificial intelligence in breast imaging : Areas of application from a clinical perspective].

Authors:  Pascal A T Baltzer
Journal:  Radiologe       Date:  2021-01-28       Impact factor: 0.635

Review 3.  The Artificial Intelligence in Digital Radiology: Part 1: The Challenges, Acceptance and Consensus.

Authors:  Daniele Giansanti; Francesco Di Basilio
Journal:  Healthcare (Basel)       Date:  2022-03-10
  3 in total

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