Meddies/meddies-pii-v2
https://huggingface.co/Meddies/meddies-pii-v2A 350M encoder that finds nine types of personally identifiable information across 17 languages and returns exact character spans for review and redaction.
Sourced from
- HuggingFace — Meddies/meddies-pii-v2
Related resources
genzeonplatform/healthcare-brain-ner
by genzeonplatformHealthcare Brain NER is a transformer-based clinical Named Entity Recognition model developed by Genzeon Platforms for automated detection and de-identification of Protected Health Information (PHI) and Personally Identifiable Information (PII) in unstructured clinical text.
This model is a high-performance Named Entity Recognition (NER) model designed specifically for medical text. It identifies entities such as diseases, symptoms, procedures, medications, and healthcare providers with high precision and recall, making it ideal for clinical and healthcare applications.
genzeonplatform/cliniguard-laboratory-ner
by genzeonplatformCliniGuard Laboratory NER is a transformer-based clinical Named Entity Recognition model developed by Genzeon Platforms for automated extraction of laboratory test results, values, units, reference ranges, and abnormality flags from unstructured clinical text.
CliniGuard Clinical Findings NER is a transformer-based clinical Named Entity Recognition model developed by Genzeon Platforms for automated extraction of clinical findings, diseases, conditions, anatomical locations, and clinical modifiers from unstructured clinical text.
genzeonplatform/healthcare-brain-laboratory-ner
by genzeonplatformHealthcare Brain Laboratory NER is a transformer-based clinical Named Entity Recognition model developed by Genzeon Platforms for automated extraction of laboratory test results, values, units, reference ranges, and abnormality flags from unstructured clinical text.
genzeonplatform/cliniguard-vitals-ner
by genzeonplatformCliniGuard Vitals NER is a transformer-based clinical Named Entity Recognition model developed by Genzeon Platforms for automated extraction of vital signs, body measurements, and physiological parameters from clinical text.