SEP 9, 2026 · PREPRINT
MedDeID enables locally governed clinical-text de-identification from real or synthetic training data
arXiv
A proof-of-concept framework for clinical text de-identification with promising performance metrics on limited datasets, but lacking independent validation, clinical outcome data, and peer review.
Reported
Identification sensitivity (hospi…98.9%
Non-identifier redaction rate (ho…0.24%
Identification sensitivity (synth…96.1%