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Data · dataset · 2022

n2c2 2014 De-identification

Listed in Hugging Face Datasets

The 2014 i2b2/UTHealth Natural Language Processing (NLP) shared task featured two tracks.

Description

The first of these was the de-identification track focused on identifying protected health information (PHI) in longitudinal clinical narratives. TRACK 1: NER PHI\n HIPAA requires that patient medical records have all identifying information removed in order to protect patient privacy.

There are 18 categories of Protected Health Information (PHI) identifiers of the patient or of relatives, employers, or household members of the patient that must be removed in order for a file to be considered de-identified. In order to de-identify the records, each file has PHI marked up. All PHI has an XML tag indicating its category and type, where applicable.

Read the rest (1 more)

For the purposes of this task, the 18 HIPAA categories have been grouped into 6 main categories and 25 sub categories

Links

Where it is published

Catalogue records · 1

Topics

Inferred from text
Longitudinal study 65%
Provenance · 1 source records, 9 field assertions
SourceKeyLast seenRaw
Hugging Face Datasetsbigbio/n2c2_2014_deid15 d agoJSON v1
FieldAssertionExtractorEvidence
access_levelsource · Hugging Faceconnector:huggingface@1.0.0/gated
concepts[field].local:field:computer-science-aimapping · Hugging Faceconnector:huggingface@1.0.0
concepts[method].local:method:longitudinal-studyenrichment · Hugging Facekeyword-concept-rules@1.0.0title+description (65%)
created_datesource · Hugging Faceconnector:huggingface@1.0.0
descriptionsource · Hugging Faceconnector:huggingface@1.0.0/description
license_textsource · Hugging Faceconnector:huggingface@1.0.0
publication_datesource · Hugging Faceconnector:huggingface@1.0.0
titlesource · Hugging Faceconnector:huggingface@1.0.0/id
updated_datesource · Hugging Faceconnector:huggingface@1.0.0