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cs.CV2026
Risk-Calibrated Learning: Minimizing Fatal Errors in Medical AI
Abolfazl Mohammadi-Seif, Ricardo Baeza-Yates
Deep learning models often achieve expert-level accuracy in medical image classification but suffer from a critical flaw: semantic incoherence. These high-confidence mistakes that…
cs.CV2026
Face Density as a Proxy for Data Complexity: Quantifying the Hardness of Instance Count
Abolfazl Mohammadi-Seif, Ricardo Baeza-Yates
Machine learning progress has historically prioritized model-centric innovations, yet achievable performance is frequently capped by the intrinsic complexity of the data itself. In…