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InfoResearchPreprintLLM-specific
EdgeDeID: A 0.6B Clinical De-identifier Trained Without Real Patient Data
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Summary
EdgeDeID is a 0.6B-parameter decoder-only clinical de-identifier trained entirely on synthetic notes, with no real patient text. It reaches 0.994 micro-F1 on a 100-note synthetic benchmark, against 0.857 for the strongest of eight off-the-shelf systems, and drops to 0.48 F1 on MIMIC ICU nursing notes. Three hand-written in-context examples recover 0.08 F1 without annotated target data.