SF 19 - Big data use and governance: top tips for radiographers
ECR 2021
3Lectures
44Minutes
3Speakers
Lectures
1
SF 19 - What can big data tell us about our clinical services? Leveraging data from the Scottish National PACS
15:44J. McConnell, Glasgow / UK
Learning Objectives 1. To understand the types of data and data assimilations undertaken. 2. To become familiar with the analysis processes. 3. To consolidate knowledge about the outcomes and impact of big data analysis. 4. To learn how radiographers can get involved with similar initiatives.
2
SF 19 - How do you manage and protect all that data? Learning from multicentre studies
13:35M. McEntee, Cork / IE
Learning Objectives 1. To understand data protection principles, data security, and encryption. 2. To appreciate the processes for data sharing 3. To learn about the communication between systems when a patient opts-out of data sharing.
3
SF 19 - Artificial intelligence (AI): data-driven decision making in imaging
15:05R. Decoster, Brussels / BE
Learning Objectives 1. To learn about the applications of AI for radiography. 2. To become familiar with the data-driven decisions. 3. To consolidate knowledge about ethics ad responsibilities for AI decision-making. 4. To understand the potential augmentation of the radiographer’s role.
Description
SF 19-3
15 min
What can big data tell us about our clinical services? Leveraging data from the Scottish National PACS
Jonathan McConnell, Glasgow / United Kingdom
Learning Objectives
1. To understand the types of data and data assimilations undertaken. 2. To become familiar with the analysis processes. 3. To consolidate knowledge about the outcomes and impact of big data analysis. 4. To learn how radiographers can get involved with similar initiatives.
SF 19-4
15 min
How do you manage and protect all that data? Learning from multicentre studies
Mark F. F. McEntee, Cork / Ireland
Learning Objectives
1. To understand data protection principles, data security, and encryption. 2. To appreciate the processes for data sharing 3. To learn about the communication between systems when a patient opts-out of data sharing.
SF 19-5
15 min
Artificial intelligence (AI): data-driven decision making in imaging
Robin Germain Lucien Decoster, Brussels / Belgium
Learning Objectives
1. To learn about the applications of AI for radiography. 2. To become familiar with the data-driven decisions. 3. To consolidate knowledge about ethics ad responsibilities for AI decision-making. 4. To understand the potential augmentation of the radiographer’s role.
10 min
Live Q&A: Should radiographers evolve to be clinical imaging computer/data scientists?
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