Investigating Trustworthiness of Nonparametric Deep Survival Models for Alzheimer's Disease Progression Analysis

This research investigates the trustworthiness and fairness of nonparametric deep survival models for analyzing Alzheimer's Disease (AD) progression. It addresses the lack of studies considering learned bias in existing deep learning models for AD and proposes novel fairness metrics to ensure reliable predictions.