ESR meets the United States

Meets 5a - RSNA and ACR AI initiatives: perspectives and insights

Lectures

1
Chairpersons' introduction

Chairpersons' introduction

05:00Minerva Becker, Geneva / CH, Jeffrey Klein, Williston / US, Alan H Matsumoto, Reston / US

2
Research and education in AI: RSNA initiatives

Research and education in AI: RSNA initiatives

10:00Jeffrey Klein, Williston / US

3
Implementation of AI tools: a U.S. radiology department chair’s perspective

Implementation of AI tools: a U.S. radiology department chair’s perspective

10:00Jorge A Soto, Boston / US

4
Musical interlude

Musical interlude

02:00Musical interlude

5
The U.S.’s first national post-deployment AI monitoring program in radiology: learning from the ACR experience

The U.S.’s first national post-deployment AI monitoring program in radiology: learning from the ACR experience

10:00Alan H Matsumoto, Reston / US

6
Inside the healthcare AI arena: ACR's insights on generative AI for radiology

Inside the healthcare AI arena: ACR's insights on generative AI for radiology

10:00Christoph Wald, Rochester / US

7
Panel discussion: What can we learn from U.S. societal efforts to employ AI in radiology?

Panel discussion: What can we learn from U.S. societal efforts to employ AI in radiology?

13:00Panel discussion: What can we learn from U.S. societal efforts to employ AI in radiology?

5 min
Chairpersons' introduction
Minerva Becker, Geneva / Switzerland
Jeffrey Klein, Williston / United States
Alan H Matsumoto, Reston / United States
10 min
Research and education in AI: RSNA initiatives
Jeffrey Klein, Williston / United States
  1. To identify the use of data science challenges and medical imaging resources in furthering AI development in our speciality.
  2. To create programs to educate radiologists in AI.
  3. To apply the use of the CLAIM guidelines in standardising the reporting of AI science.
10 min
Implementation of AI tools: a U.S. radiology department chair’s perspective
Jorge A Soto, Boston / United States
  1. To identify operational and financial considerations for selecting AI solutions.
  2. To describe factors that affect the implementation of AI in academic practice.
  3. To define the various clinical, organisational and educational applications of AI in academic radiology.
2 min
Musical interlude
10 min
The U.S.’s first national post-deployment AI monitoring program in radiology: learning from the ACR experience
Alan H Matsumoto, Reston / United States
  1. To understand the importance of having a governance structure for your AI portfolio.
  2. To detail the ACR Recognition for Health Care (ARCH) AI program.
  3. To detail what the ACR has learned from its experience with its post-deployment AI monitoring approach (Assess-Ai registry).
10 min
Inside the healthcare AI arena: ACR's insights on generative AI for radiology
Christoph Wald, Rochester / United States
  1. To describe the ACR experience of using generative AI in operating a post-deployment monitoring system.
  2. To review healthcare AI challenges: experience and insights from crowdsourced testing of generative AI models on common radiology tasks.
  3. To detail the use of generative AI in nonclinical and clinical tasks.
13 min
Panel discussion: What can we learn from U.S. societal efforts to employ AI in radiology?

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