-How generative AI can address fundamental challenges of AI in healthcare, including limited data sets and privacy restrictions.
-The potential of synthetic medical images to support fairer and more generalizable models and improve diagnostic workflows in radiology and oncology.
-Current limitations and open challenges in evaluating generative models, including clinical relevance, realism, and unintended artifacts.
-Learn about practical applications of synthetic data in clinical trial design, patient simulation, and rare disease research.
-Discuss key challenges, including regulatory acceptance, data quality validation, and ethical considerations.
-Share strategies for integrating synthetic datasets to improve model training, study diversity, and data protection.
Check out the incredible speaker line-up to see who will be joining Elmar.
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