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Five key takeaways about AI from RSNA

por John W. Mitchell, Senior Correspondent | November 28, 2018
Artificial Intelligence

4 – Hospital administration cannot afford AI for the sake of AI
Administrators who pay for things in hospitals are mostly interested in immediate, low-hanging fruit. They are not interested in paying for "toys," so pitching AI for AI's sake will not be a successful strategy. Rather, radiologists must speak the language of administrators. This includes AI spending for better efficiency, reducing costs, increasing output and getting better outcomes. Start building IT and informatics infrastructure now, which is the "road" for AI to travel.

5 – Keep AI in proper perspective.
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It will not replace radiologists but augment them. AI is neither a horrible threat nor a promised savior. Radiologists need help to meet the growing burden of workloads, expectations for quality, and cost control. AI machine learning applications are a viable solution.

Radiology has always been a leader in adopting disruptive technology, and AI is no different. Radiologists should devote some of their CME learning to understanding the use of algorithms in their practice. Such training is offered through several entities, including RSNA. Chang quoted Mark Zuckerberg on a critical truth: "The best AI-powered systems require humans to play an active role in their creation, tending and operation."

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