ESR/ESOR AI - 3 - Clinical applications

• to become familiar with the opportunities of multiparametric prostate MRI (mpMRI) that improve early detection and personalised treatment of prostate cancer

• to understand the essential issue of prostate mpMRI that limit widespread use in clinical practice

• to learn about the principles, opportunities and initial developments of deep learning algorithms that could significantly improve standardised, objective and quantitative prostate mpMRI in the clinical workflow

• to learn about current technical developments of AI in rectal cancer
• to become familiar with the most important clinical results
• to understand the rationale and value of AI-based decision support algorithms in rectal cancer

• to review the existing applications of AI in liver imaging

• to provide an overview of the future potential clinical applications of AI in liver imaging

• to foresee if and how AI will impact the role of the radiologist expert in liver imaging vs clinicians and patients

• to understand the evolution computer aid in breast imaging

• to learn about the performance of AI algorithms for relevant applications in breast imaging

• to provide an overview of the future potential clinical applications of AI in breast imaging

• to learn about the performance of AI for nodule detection and characterisation

• to learn about the performance of AI for lung cancer diagnosis on lung cancer screening datasets

• to learn about the performance of AI for predicting response to treatment

• to understand the principles and potential of quantitative tumour imaging and radiomics

• to become familiar with the ‘state-of-the-art’ machine learning and AI techniques in neuro-oncology imaging

• to know the most common and recent applications of AI in neuro-oncology

• to understand the value of AI-driven diagnosis and prognosis in neuro-oncology