AI in radiology education
December 05, 2019

DOTMed: How Does AI Fit Into Radiology Education

The adoption of artificial intelligence (AI) faces various challenges, from governance to how radiology residents learn about the technology.

A panel of experts brought up a number of ideas to address these challenges during a discussion of AI at the RSNA annual meeting, including creating public/private partnerships and promoting independent learning through video.

Dr. Mark Mullins, professor and vice chair of education at Emory Radiology, spoke about the importance of partnerships between private industry and academia to lead the adoption of AI.

“I have seen many things develop in the absence of real-life experience and it isn’t quite as good,” Mullins said. “You need someone involved who knows where the applications are. In the big picture, this could give back a lot of time, effort and energy to practicing physicians.”

Janak Joshi, the senior vice president and chief technology officer of Life Image, a medical image and patient information sharing company, noted that part of the challenge of AI adoption is sorting through the explosion of AI providers, many of which offer similar solutions.

“I was roaming around the show floor downstairs in the AI pavilion and I counted about 28 companies who can do lung cancer detection of some sort,” Joshi said. “They all said that they were unique. They all trained their data probably on the data set coming from the National Cancer Institute. And each one of them said, ‘We are better than the other person.’ So how can 28 companies be different? Who here is saying that ‘I’m going to be the validation partner’ and ‘I’m going to be the one saying that every one of these guys is right’? So that’s part of the challenge for who should tackle this.”

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