E³ - Advanced Courses
E³ 622 - Challenges and solutions for introducing artificial intelligence (AI) in daily clinical workflow
Lectures
E³ 622 - A. Implementation of AI algorithms in picture archiving and communication systems (PACS)
13:21W. Veldhuis, Utrecht / Netherlands
Learning Objectives
1. To learn about how to start experimenting with AI in daily clinical routine.
2. To learn about the developments of integrating multiple AI tools within one framework.
3. To learn about the processes to evaluate AI algorithms for clinical use cases.
E³ 622 - B. How to best complement human intelligence with AI
10:32C. Herold, Vienna / Austria
Learning Objectives
1. To understand the current and emerging concept for AI and machine learning in imaging.
2. To explore whether it is possible to successfully integrate AI into clinical practice today.
3. To learn how radiologists can be assisted by AI.
E³ 622 - C. AI, ethics, and radiology
15:02A. Brady, Cork / Ireland
Learning Objectives
1. To understand the 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 622 - D. AI in radiology: culture change
14:47H. Fleishon, Atlanta, GA / United States
Learning Objectives
1. To review the possible changes in radiology practices and departments due to the implementation of AI workflows.
2. To present the possible impact of AI on radiology macroeconomics.
3. To discuss the educational innovations in introducing AI into radiology resident training.
2. To learn about the developments of integrating multiple AI tools within one framework.
3. To learn about the processes to evaluate AI algorithms for clinical use cases.
2. To explore whether it is possible to successfully integrate AI into clinical practice today.
3. To learn how 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 the possible impact of AI on radiology macroeconomics.
3. To discuss the educational innovations in introducing AI into radiology resident training.