「de-identification」の検索結果

Implements HIPAA de-identification methods under 45 CFR §164.514(a)-(b). Covers expert determination method and safe harbor method with 18 identifiers removal, re-identification risk assessment, limited dataset requirements, and data use agreements. Keywords: HIPAA de-identification, safe harbor, expert determination, 18 identifiers, limited dataset, PHI.

日本語の概要は準備中です。原文の説明を表示しています。

Implement the NIST Privacy Framework CONTROL function covering CT.DM data management, CT.DP data processing policies and procedures, and CT.PO disassociated processing. Provides technical control architectures, data management workflows, and de-identification implementation guidance.

日本語の概要は準備中です。原文の説明を表示しています。

Evaluates anonymization as a retention alternative under GDPR Recital 26, applying the WP29 Opinion 05/2014 techniques including randomization and generalization. Validates anonymization effectiveness using k-anonymity, l-diversity, and t-closeness metrics. Activate for anonymization, de-identification, k-anonymity, retention alternative queries.

日本語の概要は準備中です。原文の説明を表示しています。

Reads, inspects, writes, transforms, and preflights local DICOM datasets and pixel data. Applies to DICOM metadata, transfer syntaxes, compression plugins, frames, private elements, JSON, and bounded de-identification review.

日本語の概要は準備中です。原文の説明を表示しています。

Used for header-only preflight of one DICOM series folder before conversion or inference. Not for de-identification or clinical clearance.

日本語の概要は準備中です。原文の説明を表示しています。

Peptide-spectrum matching and protein identification from MS/MS data. Use when identifying peptides from tandem mass spectra. Covers database searching, spectral library matching, and FDR estimation using target-decoy approaches.

日本語の概要は準備中です。原文の説明を表示しています。

Clinical-grade PII/PHI detection and de-identification for healthcare text data. Scans all 18 HIPAA identifier categories with confidence scoring, generates audit logs, supports custom regex patterns, and produces de-identified output while preserving document structure.

日本語の概要は準備中です。原文の説明を表示しています。

Expert knowledge for Azure Health Data Services development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when using FHIR/DICOM APIs, bulk import/export, de-identification, events, or Synapse/Data Lake integrations, and other Azure Health Data Services related development tasks. Not for Azure Health Bot (use azure-health-bot), Azure Data Manager for Agriculture (use azure-data-manager-for-agri), Azure Energy Data Services (use azure-energy-data-services).

日本語の概要は準備中です。原文の説明を表示しています。

HIPAA compliance - PHI protection, technical/administrative/physical safeguards, minimum necessary standard, BAA requirements, de-identification, access logging

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Implements HIPAA Privacy Rule requirements for research uses of protected health information under 45 CFR §164.512(i). Covers IRB and Privacy Board waivers of authorization, individual authorization for research, limited data set and data use agreements, preparatory to research provisions, and decedent research provisions. Keywords: HIPAA research, IRB waiver, Privacy Board, authorization, limited data set, preparatory research, de-identification, Common Rule.

日本語の概要は準備中です。原文の説明を表示しています。

NLP on clinical text — de-identification, concept extraction, phenotyping from notes, and LLM safety guardrails.

日本語の概要は準備中です。原文の説明を表示しています。

Use before sensitive, clinical, identifying, or raw interview data is placed in front of an AI tool, when transcripts or student materials need de-identification, or when a data-minimization gate must run before any analysis or drafting.

日本語の概要は準備中です。原文の説明を表示しています。