Refresher Courses: Oncologic Imaging

Artificial intelligence in oncologic imaging: ready for prime time?

March 2, 00:00 - 00:00 CET

5 min
Chairperson's introduction
10 min
Artificial intelligence frontiers in oncologic screening
1. To learn about the features and scientific evidence of commercially available artificial intelligence solutions in oncological screening.
2. To learn about the different strategies for workflow integration of artificial intelligence solutions in screening.
3. To learn about the current research algorithms for oncological screening and unmet needs.
10 min
Artificial intelligence tumour characterisation: challenges and future prospective
1. To define the best methodology approaches for artificial intelligence developments in tumour characterisation and aggressiveness estimations.
2. To describe the challenges regarding data extraction, data curation, datasets partitions, and standardisation on estimated outputs.
3. To discuss the main solutions for data undersampling, data harmonisation, general context integration, biological correlation, improved reproducibility, and continuous learning.
10 min
Radiomics and data integration
1. To name and describe the main challenges for multi-dimensional data integration.
2. To describe the most widely used technologies for radiomic data extraction.
3. To differentiate between different machine learning methods for data integration and to identify opportunities for development.
10 min
Imaging biobanks for artificial intelligence improvement
1. To understand how collaborative efforts in data sharing may help to improve the performance of artificial intelligence models that reach clinical use.
2. To learn how to differentiate centralised repository strategies versus federated learning.
3. To discover how to combine multi-omics information in specific platforms for collaborative research in artificial intelligence and medical imaging.
15 min
Panel discussion: Can artificial intelligence improve the oncologic multidisciplinary team?