Privacy-Preserving Active Learning for precision oncology clinical workflows for extreme data sparsity scenarios

The author recounts their struggle to develop a precision oncology model for rare pediatric sarcoma, facing extreme data sparsity (47 samples) and strict HIPAA/GDPR constraints that prevented data sharing across institutions. This personal journey underscores the critical need for privacy-preserving active learning to address these challenges in real-world clinical workflows.