United States newspaper and online media coverage of artificial intelligence and radiology from 1998 to 2023.

Autor: Zippi ZD; Florida International University College of Medicine, United States of America., Cortopassi IO; Mayo Clinic Florida and Mayo Clinic College of Medicine and Science, United States of America., Grage RA; Mayo Clinic Florida and Mayo Clinic College of Medicine and Science, United States of America., Johnson EM; Mayo Clinic Florida and Mayo Clinic College of Medicine and Science, United States of America., McCann MR; Mayo Clinic Florida and Mayo Clinic College of Medicine and Science, United States of America., Mergo PJ; Mayo Clinic Florida and Mayo Clinic College of Medicine and Science, United States of America., Sonavane SK; Mayo Clinic Florida and Mayo Clinic College of Medicine and Science, United States of America., Stowell JT; Mayo Clinic Florida and Mayo Clinic College of Medicine and Science, United States of America., White RD; Mayo Clinic Florida and Mayo Clinic College of Medicine and Science, United States of America., Little BP; Mayo Clinic Florida and Mayo Clinic College of Medicine and Science, United States of America. Electronic address: little.brent@mayo.edu.
Jazyk: angličtina
Zdroj: Clinical imaging [Clin Imaging] 2024 Sep; Vol. 113, pp. 110238. Date of Electronic Publication: 2024 Jul 20.
DOI: 10.1016/j.clinimag.2024.110238
Abstrakt: Objective: To evaluate the frequency and content of media coverage pertaining to artificial intelligence (AI) and radiology in the United States from 1998 to 2023.
Methods: The ProQuest US Newsstream database was queried for print and online articles mentioning AI and radiology published between January 1, 1998, and March 30, 2023. A Boolean search using terms related to radiology and AI was used to retrieve full text and publication information. One of 9 readers with radiology expertise independently reviewed randomly assigned articles using a standardized scoring system.
Results: 379 articles met inclusion criteria, of which 290 were unique and 89 were syndicated articles. Most had a positive sentiment (74 %) towards AI, while negative sentiment was far less common (9 %). Frequency of positive sentiment was highest in articles with a focus on AI and radiology (86 %) and lowest in articles focusing on AI and non-medical topics (55 %). The net impact of AI on radiology was most commonly presented as positive (60 %). Benefits of AI were more frequently mentioned (76 %) than potential harms (46 %). Radiologists were interviewed or quoted in less than one-third of all articles.
Conclusion: Portrayal of the impact of AI on radiology in US media coverage was mostly positive, and advantages of AI were more frequently discussed than potential risks. However, articles with a general non-medical focus were more likely to have a negative sentiment regarding the impact of AI on radiology than articles with a more specific focus on medicine and radiology. Radiologists were infrequently interviewed or quoted in media coverage.
Competing Interests: Declaration of competing interest Richard D. White MD reports a relationship with AIDOC that includes: consulting or advisory. Richard D. White MD reports a relationship with Siemens Healthineers that includes: funding grants. Richard D. White MD has patent LLIED Model pending to Patent pending. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2024 Elsevier Inc. All rights reserved.)
Databáze: MEDLINE
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