Researchers led by Julia Goldberg of NYU Langone Health searched Twitter for all tweets that included the terms "artificial intelligence" and "radiology" between November 2016 and October 2017. Nearly 90% of tweets that included links to websites leaned toward the position that AI was positive for the field of radiology, they found.
What's more, more than 75% of tweets that linked to websites and discussed the possibility of AI replacing radiologists were found to favor the job security of radiologists.
"This study reveals a generally optimistic opinion on Twitter regarding the impact of AI on radiology, especially when considering workflow improvements," the authors wrote. "While noting challenges, these social media discussions were overwhelmingly positive toward the transformative impact of AI on radiology and leaned against AI replacing radiologists."
Of the 605 tweets, 407 were from unique users -- most often industry-related individuals (22.6%). Overall, 24.6% of the tweets took the position that AI was favorable for radiology, while 75.4% were neutral. None of the tweets viewed AI's impact on radiology unfavorably.
The tweets included a total of 216 unique links to websites, including radiology media (24.1%), healthcare media (24.1%), a nonmedia healthcare-related organization (14.4%), mainstream media (13.9%), and technology/data media (10.2%). Of these linked websites, 88% leaned toward AI being positive for radiology, while none were negative for the field. In addition, 51.9% of the linked websites highlighted AI's perceived benefit of improved efficiency for radiology; 35.2% pointed to challenges for implementing AI in radiology.
The possibility of AI replacing radiologists was discussed on 47.3% of the linked websites in the tweets.
|What is Twitter saying about whether AI will replace radiologists?
|Content of websites linked from Twitter
|AI will not replace radiologists
|AI will replace radiologists
Over time, the further development and clinical implementation of AI will likely change the conversations about the role of AI in radiology, according to the researchers.
"Even within the one-year time period of this study, the frequency of tweets that leaned toward AI having a favorable impact on radiology increased slightly from the first six-month period to the second six-month period, which may reflect broader shifts in public opinion on this topic," they wrote.
Goldberg and colleagues noted that the stances and themes in the social media conversations may reflect broader awareness on the topic and shifts in public opinion that have taken place since the advent of AI in medicine.
"Radiologists are encouraged to recognize the role of these public conversations and to engage widely with such discussions regarding AI in radiology," they wrote.
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