Multi-modal data integration using AI

About the event

Join us for an in-depth exploration of how artificial intelligence is transforming multi-modal data integration - the process of combining diverse data types such as genomics, medical imaging, clinical records, and wearable device outputs into unified analytical models. By leveraging machine learning and deep learning, AI can capture complex relationships across heterogeneous sources, tackling challenges of scale, noise, and dimensionality.

This integrative approach enhances disease prediction, patient stratification, and biomarker discovery in healthcare, while also enabling breakthroughs in finance, social sciences, and engineering. We’ll discuss state-of-the-art AI frameworks, including representation learning and graph-based methods, that drive more accurate, interpretable, and personalised insights.

In this session, we’ll discuss some of the key case studies and approaches demonstrating how multi-modal integration is advancing data-driven research and innovation.

Our interactive webinar will take place on Tuesday 25th November, 6-7pm (GST)

This event will take place on Zoom and a link will be shared nearer the time.