This post was contributed by ACR Executive Vice President and Chief Information Officer Mike Tilkin.
Artificial Intelligence for medical imaging is nowhere near the “Star Trek” scenario where machines autonomously diagnose and treat patients. The technological and regulatory challenges to that potential future remain immense.
What is near is AI helping radiologists make better, more efficient diagnoses as part of the next generation of clinical decision support tools. This was the consensus among AI scientists, vendors and researchers in Reston this week for the ACR Data Science Institute (DSI) Summit.
One of the ACR DSI primary missions is to promote strategies that enable vendors to leverage emerging AI technologies to help radiologists help patients. To do this, the DSI needs to engage vendors and other stakeholders early in the process. That is what we are doing. And we learned from the summit that this is what they want too.
There is a great desire for close radiologist involvement in defining the use cases, establishing the criteria for validation, and ensuring a useful clinical pathway for incorporation into the radiology workflow.
The DSI is committed to work in all of these areas, and the discussion confirmed that we are headed in the right direction. More of these summits will be scheduled in the near future to ensure continued communication and collaboration in this emerging area.
Imaging AI has the potential to be an important tool in the radiologist’s advanced technology toolkit. Working together with all stakeholders, including patients, we are moving imaging AI forward. We can and will make medicine better.
- What are some use cases where you see that imaging AI can help radiologists do their jobs better (more efficiently)?
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