Cited by 23Artificial Intelligence in Healthcare and EducationRadiomics and Machine Learning in Medical ImagingRadiology practices and education

Artificial Intelligence and Radiology: Have Rumors of the Radiologist's Demise Been Greatly Exaggerated?

Nawrocki, Tomer, Maldjian, Pierre D., Slasky, Shira E., Contractor, Sohail G.·2018·Academic Radiology

Integrity signals

Registry

Crossref · 10.1016/j.acra.2017.12.027

Cites

30 of 30 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • While the possibility of AI replacing radiologists was extensively mentioned in recent radiology publications, none of the interviewees in this research identified with this threat.

    “While the possibility of AI replacing radiologists, and thereby threatening their professional identity, was extensively mentioned in many recent radiology publications [5, 9, 16, 44], none of the interviewees in this research identified with this threat.”

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Nawrocki, T., Maldjian, P. D., Slasky, S. E., & Contractor, S. G.
Affiliations
Rutgers New Jersey Medical School (US)
Corresponding author
Nawrocki, Tomer
Venue
Academic Radiology
Publisher
Elsevier BV
Published
2018-08
Volume
25
Issue
8
Pages
967-972
ISSN
1076-6332 (ISSN-L)
OpenAlex
W2791125561
Cited by
23
References
30
Citations by year
2024: 3 · 2023: 3 · 2022: 4 · 2021: 7 · 2020: 3 · 2019: 2 · 2018: 1
FWCI
0.88
Type
journal article
Language
en
Open access
closed
Locations
Academic Radiology (publishedVersion)
Topics
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Radiomics and Machine Learning in Medical Imaging
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Radiology practices and education
Keywords
artificial intelligence in radiology, machine learning, deep learning, image recognition, digital imaging, future of radiology, radiologist role, AI adoption in medicine

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review