Analyzing Causal Fallacies in Medical Diagnostic Models Through Innovative Methods

This research explores causal reasoning and adversarial sample generation to identify fallacies in medical diagnostic models. By validating a new method through experiments on public datasets, we aim to enhance model performance and expose critical flaws, offering a comparative analysis with traditional techniques for improved diagnostics.