Challenges and solutions for introducing artificial intelligence (AI) in daily clinical workflow
Lectures
E3 720 - A. Implementation of AI algorithms in picture archiving and communication systems (PACS)
09:04W. B. Veldhuis, Utrecht / NL
Learning Objectives
1. To learn about how you can start experimenting with AI in daily clinical routine.
2. To learn about developments to integrate multiple AI tools within one framework.
3. To learn about processes to evaluate AI algorithms for clinical use cases.
E³ 720 - B. How to best complement human intelligence with AI
10:32C. J. Herold, Vienna / AT
Learning Objectives
1. To understand current and emerging concept for AI and machine learning in imaging.
2. To explore whether it is possible to success fully integrate AI into clinical practice today.
3. To learn how the radiologists can be assisted by AI.
E3 720 - C. AI, ethics and radiology
11:40A. Brady, Cork / IE
Learning Objectives
1. To understand ethical aspects related to data use in AI.
2. To learn about possible bias in AI algorithms.
3. To learn how to prepare radiology policies for AI.
E3 720 - D. AI in radiology - Culture change
07:36H. Fleishon, Atlanta, GA / US
Learning Objectives
1. To review possible changes in radiology practices and departments due to implementation of AI workflows.
2. To present possible impact of AI on radiology macroeconomics.
3. To discuss educational innovations to introduce AI into radiology resident training.
2. To learn about developments to integrate multiple AI tools within one framework.
3. To learn about processes to evaluate AI algorithms for clinical use cases.
2. To explore whether it is possible to success fully integrate AI into clinical practice today.
3. To learn how the radiologists can be assisted by AI.
2. To learn about possible bias in AI algorithms.
3. To learn how to prepare radiology policies for AI.
2. To present possible impact of AI on radiology macroeconomics.
3. To discuss educational innovations to introduce AI into radiology resident training.
