![ESMO-Webinar-series-Applications-and-Promises-of-AI-in-Oncology-1000x250](/var/esmo/storage/images/media/esmo/meetings/2024/_webinars/images/webinar-series/real-world-data-and-digital-oncology/esmo-webinar-series-applications-and-promises-of-ai-in-oncology-1000x250/18719216-2-eng-GB/esmo-webinar-series-applications-and-promises-of-ai-in-oncology-1000x250_i770.jpg)
Login to get immediate access to this content.
LoginLearning 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.