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

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Overview

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Explore how AI and continual learning can revolutionize MRI diagnostics through a real-world case study in detecting Focal Cortical Dysplasias (FCD)—a crucial factor in epilepsy treatment. 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. Learn about challenges like catastrophic forgetting, maintaining model performance in dynamic environments, and discover 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.

Syllabus

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

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