Medical Entity Codification

Map free-text medical entities to standardised ontology codes — SNOMED CT, LOINC, ICD-10-CM and Eka’s medication database.

Overview

The Medical Entity Codification API (MedLink Named Entity Linking) takes a free-text medical entity — a symptom, diagnosis, lab test or drug — and links it to the matching code in a standardised clinical ontology.

It powers structured, interoperable medical data: turning "chest pain" into SNOMED CT 29857009, "hemoglobin" into LOINC 718-7, or "type 2 diabetes mellitus" into ICD-10-CM E11.

This API supersedes the legacy GET /eka-mcp/linking/v1/snomed endpoint. See that page for a migration guide; the legacy endpoint remains operational for existing integrations.

Base URL

All endpoints are served under:

https://api.eka.care/med-link/

Authentication

Every request requires a Bearer access token:

Authorization: Bearer <access_token>

Generate the token using the Eka authorization flow — see Authorization.

Supported ontologies

Ontology	ontology	version	Use it for	metadata
SNOMED CT	snomed	20250401_extended	Symptoms, findings, disorders, procedures	Not used
LOINC	loinc	v1.0	Lab tests and observations	Recommended
Medication	medication	v5.0	Branded and generic drugs	Optional
ICD-10-CM (Comprehend)	icd-10-cm	comprehend	Diagnoses from natural-language clinical text	Not used

Always call List Registry to confirm the live ontology and version values before linking.

Endpoints

List Registry

Discover available ontologies, versions and indexes.

Link Entity

Link a single medical entity to ontology codes.

Link Entities (Batch)

Link up to 5 entities in a single call.

The metadata field

metadata carries ontology-specific hints that improve linking accuracy:

• LOINC — strongly recommended. A unit or specimen can change which code is linked (e.g. blood vs. urine hemoglobin).
• Medication — optional. form, generic_name and dose_unit help resolve ambiguous brand names.
• SNOMED CT and ICD-10-CM Comprehend — metadata is ignored.

See each endpoint page and the ontology guides in Eka MedAI → AI Technologies → Medical Entity Codification for details.

Reading a result

Each candidate in results carries:

• term_id — the ontology code
• term_name — the human-readable term
• score — relevance/confidence (null for medication)
• is_linked — true when the pipeline is confident this is the single correct match
• metadata — ontology-specific detail about the candidate