Enhancing Medical Data Imputation Using a Denoising Autoencoder with Missing-Neighborhood Perturbation.
In real-world clinical settings, the diverse types and unknown causes of missing data in tabular medical datasets pose significant challenges for accurate imputation. In particular, non-random missingness-where missing values are related to unobserved variables-limits the effectiveness of many existing imputation model...