Diagnostic Imaging December 8, 2021
Technologies must be integrated with existing platforms and workflows, as well as demonstrate value.
The journey to widespread artificial intelligence (AI) adoption in radiology has, surprisingly, taken longer than many of us had hoped and anticipated. Many in the industry have learned with experience that this journey is not a sprint, but a rather a marathon with a relay-race component, because it requires a broad ecosystem of stakeholders committed to teamwork and collaboration. As a result, the industry’s perspective on AI in radiology is continuously evolving and maturing.
Five years ago, people were focused on how AI could address and relieve physician burnout, by helping the radiologist who was facing an ever-expanding workload. But, despite intense levels of...
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