Wednesday 

Room 1 

13:40 - 14:40 

Session (60 min)

Building Adaptive AI for MRI Diagnostics: A Continual Learning Case Study

Explore how AI and continual learning can revolutionize MRI diagnostics, using our real-world case study in detecting Focal Cortical Dysplasias (FCD)—a crucial factor in epilepsy treatment. In this session, we’ll dive into how continual learning techniques, inspired by human adaptability, help AI models improve diagnostic accuracy, minimize false positives, and handle evolving data in medical settings. We’ll discuss challenges like catastrophic forgetting, maintaining model performance in dynamic environments, and practical strategies that developers can apply to other domains. Gain hands-on insights into building resilient AI systems that evolve and adapt to new data, ensuring long-term reliability in critical applications.

AI
Architecture
Machine Learning
Agata Chudzińska

Agata Chudzińska

Agata specializes in the practical application of AI to solve real-world challenges. Currently, she holds the roles of CTO and AI Solutions Architect at the Hamburg-based AI consulting company theBlue.ai. With over 8 years of professional experience in AI and data-related fields, Agata has developed AI-based solutions for a diverse range of clients, from emerging startups to global companies.