Literature DB >> 34350411

Do We Expect More from Radiology AI than from Radiologists?

Maciej A Mazurowski1.   

Abstract

The expectations of radiology artificial intelligence do not match expectations of radiologists in terms of performance and explainability. 2021 by the Radiological Society of North America, Inc.

Keywords:  Ethics; Technology Assessment

Year:  2021        PMID： 34350411      PMCID： PMC8328102          DOI： 10.1148/ryai.2021200221

Source DB:  PubMed          Journal:  Radiol Artif Intell        ISSN： 2638-6100


  9 in total

1.  BI-RADS lexicon for US and mammography: interobserver variability and positive predictive value.

Authors:  Elizabeth Lazarus; Martha B Mainiero; Barbara Schepps; Susan L Koelliker; Linda S Livingston
Journal:  Radiology       Date:  2006-03-28       Impact factor: 11.105

Review 2.  Deep learning in radiology: An overview of the concepts and a survey of the state of the art with focus on MRI.

Authors:  Maciej A Mazurowski; Mateusz Buda; Ashirbani Saha; Mustafa R Bashir
Journal:  J Magn Reson Imaging       Date:  2018-12-21       Impact factor: 4.813

3.  Artificial Intelligence May Cause a Significant Disruption to the Radiology Workforce.

Authors:  Maciej A Mazurowski
Journal:  J Am Coll Radiol       Date:  2019-04-08       Impact factor: 5.532

4.  Will Artificial Intelligence Replace Radiologists?

Authors:  Curtis P Langlotz
Journal:  Radiol Artif Intell       Date:  2019-05-15

5.  AI Hype and Radiology: A Plea for Realism and Accuracy.

Authors:  John Banja
Journal:  Radiol Artif Intell       Date:  2020-07-01

6.  Interobserver Variability of Sonographic Features Used in the American College of Radiology Thyroid Imaging Reporting and Data System.

Authors:  Jenny K Hoang; William D Middleton; Alfredo E Farjat; Sharlene A Teefey; Nicole Abinanti; Fernando J Boschini; Abraham J Bronner; Nirvikar Dahiya; Barbara S Hertzberg; Justin R Newman; Daniel Scanga; Robert C Vogler; Franklin N Tessler
Journal:  AJR Am J Roentgenol       Date:  2018-04-27       Impact factor: 3.959

7.  Artificial Intelligence and the Practice of Radiology: An Alternative View.

Authors:  Robert Schier
Journal:  J Am Coll Radiol       Date:  2018-05-11       Impact factor: 5.532

8.  Artificial Intelligence in Radiology: Some Ethical Considerations for Radiologists and Algorithm Developers.

Authors:  Maciej A Mazurowski
Journal:  Acad Radiol       Date:  2020-01       Impact factor: 3.173

9.  A survey on the future of radiology among radiologists, medical students and surgeons: Students and surgeons tend to be more skeptical about artificial intelligence and radiologists may fear that other disciplines take over.

Authors:  Jasper van Hoek; Adrian Huber; Alexander Leichtle; Kirsi Härmä; Daniella Hilt; Hendrik von Tengg-Kobligk; Johannes Heverhagen; Alexander Poellinger
Journal:  Eur J Radiol       Date:  2019-11-09       Impact factor: 3.528
  9 in total

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