Architectural Robustness to Label Noise Using Variational Quantum Circuits for Medical Image Classification

Label noise is prevalent in medical image datasets, arising from observer disagreement and ambiguous cases and deep networks memorize the mislabeled examples at the cost of generalization. Current solutions such as loss correction and sample selection add training complexity and generally assume the