Real World Data and Digital Oncology – Applications and Promises of Artificial Intelligence (AI) in Oncology: What Oncologists Need to Know

Learning objectives:

• Gain a general understanding of AI methodologies applied in medical research, particularly in the field of oncology.
• Explore the impact of AI in oncology, emphasising its ability to emulate human intelligence and analyse large datasets for predictions and conclusions.
• Recognise the significance of applying AI to cancer research due to the vast amount of data available, which conventional analysis methods may not fully utilise.
• Focus on the challenges posed by multiomics data, including variations in nature, format, and storage, and the need for specialised approaches to exploit its potential.
• Acquire knowledge of frequently used machine learning (ML) and deep learning (DL) methods, as well as Explainable AI concepts.
• Enable clinicians to identify the value of AI models in trials and studies, making patient- and tumour-related data more exploitable.
• Empower biologists to broaden their scope in tumour biology, facilitating the discovery of new biomarkers and mechanisms through the integration of AI methodologies.