Exploring Causal Fallacies in Medical Diagnostic Models Through Innovative Methods

This research combines theoretical analysis and experimental validation to uncover causal fallacies in medical diagnostic models. By proposing a new adversarial sample generation method, we aim to enhance model performance and expose weaknesses, validated through comparative experiments using public medical datasets and simulated environments.