Use Cases and Implementation Strategies for AI Rays


Charles E. Kan Jr., MDMS, editor of RSNA magazine Radiology: artificial intelligenceand Professor and Vice Chair of Radiology at the University of Pennsylvania’s Perelman School of Medicine. He has been highly involved in radiological informatics and has watched closely the evolution of radiology towards a deeper integration with Artificial Intelligence (AI).

Kan explains that there is a lot of work involved in integrating AI into radiology systems. He also said that the role of artificial intelligence is becoming more important as the United States faces a growing shortage of radiologists, and technology can help increase radiologists to do more and improve patient care.

“Every time someone comes in and asks for an AI app to be installed in the radiology department, that means someone has to get the legal agreements and all the contracting, but then you have to connect it to your systems,” Khan said.

This includes connecting it, ideally, within EMR, PACS, and other systems used in radiology. This is why many vendors are approaching the concept of an app store where a single vendor can act as a gatekeeper to facilitate the integration of a particular AI within the existing PACS system architecture.

“For departments that want to start exploring these tools, this is an expensive proposition and requires a reasonable amount of resources, not only in terms of explicit criticism of purchasing or licensing the system, but also in terms of IT support to build and maintain connections,” Kahn explained.

Another question that radiology departments need to ask is why a certain AI algorithm is adopted. Suggested use cases for AI include a way to extend screening programs or advanced image interpretations first in rural hospitals and underserved and under-resourced communities. A few years ago, it was suggested that artificial intelligence might replace radiologists, but that looks set to take decades in the future, if ever, Khan said. Instead, there is a growing shortage of radiologists, and artificial intelligence may play a role in helping radiologists so they can focus on reading suspected cases of disease or more complex cases.

Kahn also said that AI could play a major role in the coming years to address health disparities.

“On some level, we need to find ways we can provide cost-effective care, reach all the people we need to reach and provide equitable health care, and hopefully we can use AI to expand access to what we are working on,” Khan said. to improve its quality.

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