77% of radiology leaders agree AI is important for medical imaging, but adoption is low

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The majority of clinical leaders agree machine learning is important, although their organizations are still a few years away from adopting the technology, according to a Reaction Data report.

Machine learning, a type of artificial intelligence, has seen some success in helping clinicians review medical images. To assess this trend, Reaction Data surveyed radiology directors, physicians and technicians from more than 150 hospitals, clinics and imaging centers about their attitudes toward the technology.

More than three-quarters (77 percent) of respondents agree machine learning is important to the medical imaging field, compared to only 11 percent who said the technology is not important. Twelve percent of respondents were neutral.

However, only 22 percent of respondents have adopted machine learning capabilities at their organizations, with an additional 11 percent citing plans to adopt machine learning in the next 12 months. Twenty-eight percent of respondents said they are one to two years away from adopting machine learning, and 23 percent said they are more than three years away.

Sixteen percent of respondents said they will most likely never use machine learning.

Among respondents who are already using machine learning, the most popular use cases relate to lung, breast and cardiovascular imaging.

Findings for the survey were compiled from Reaction Data's Research Cloud. For additional information, please contact Erik Westerlind at ewesterlind@reactiondata.com.

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