Practical guides for hospitals, insurers and health-data teams that want to use AI models without exposing patients.
· 3 min read
What on-premise PII detection and redaction means for medical records, how it differs from cloud de-identification APIs, and the signals that you need it.
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The privacy gateway pattern: extract text, tokenize PHI locally, send only tokens to the model, and re-hydrate the answer inside your network.
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What each framework says about de-identified, pseudonymized and anonymized health data, and what that means for sending clinical text to AI models.
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Which identifiers in U.S. clinical documents generic named-entity models tend to miss, what their formats look like, and how to detect them reliably.
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A practical plan to evaluate PII redaction tools on your own clinical documents: sampling, annotation, metrics per entity type and the acceptance criterion your committee needs.
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