AP-HP/eds-pseudo-public

CliniGuard Medication NER is a transformer-based clinical Named Entity Recognition model developed by Genzeon Platforms for automated extraction of medication names, dosages, routes, frequencies, and administration details from unstructured clinical text.

Healthcare 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.

Healthcare Brain Diagnosis ICD NER is a transformer-based clinical Named Entity Recognition model developed by Genzeon Platforms for automated extraction of diagnoses, conditions, and support for ICD-10/SNOMED code mapping from 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.

CliniGuard 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.

Healthcare 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.