ESR/ESOR AI - 1 - Issues on cancer diagnostics

Learning Objectives
1. to gain an overview about some of the key deep learning methods applicable to cancer imaging
2. to appreciate the need for annotated and good-quality data for training algorithms
3. to become familiar with some exemplar applications of machine/deep learning in this domain

Learning Objectives
1. to become familiar about circulating tumour DNA determination (liquid biopsy) in patients with cancer
2. to understand how liquid biopsy can be used to rationalise treatment in operable and metastatic colorectal cancer
3. to appreciate how liquid biopsy can be leveraged to better understand the biology of colon cancer
4. to learn how liquid biopsy and radiomics can be coupled for predicting response in cancer patients

Learning Objectives
1. to understand the potential and limitations of different imaging methods in cancer detection
2. to become familiar with different advanced radiology techniques used in oncological imaging
3. to recognise the value of imaging biomarkers to predict cancer behaviour