API Catalog

Context-Aware Extraction (CAE) leverages clinical NLP to identify clinically relevant problems and conditions within unstructured clinical notes. Using contextual understanding and terminology normalization, CAE maps extracted concepts to clinician-friendly IMO terms and standardized clinical vocabularies, enabling structured, computable clinical data from free-text documentation.

The De-Identification API provides capabilities to identify and obfuscate Protected Health Information (PHI) in unstructured clinical text. It exposes a two-step flow: a PHI Identification endpoint that extracts PHI entities using IMO's Named Entity Recognition models, and a PHI Obfuscation endpoint that redacts or replaces those entities according to a configurable per-entity policy. Together these endpoints support HIPAA Safe Harbor de-identification workflows.

Natural Language Processing (NLP) provides the capability to extract entities within unstructured clinical notes using named entity recognition. The Entity Extraction API identifies clinical domain terms in unstructured clinical data recognizing IMO Problem, Procedure, Medication, and Lab domain terms. The Entity Extraction API then normalizes identified terms using IMO Precision Normalize providing users the benefit of computable, clinician-friendly IMO terms and standard clinical terminology data.