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Documentation Index

Fetch the complete documentation index at: https://developer.eka.care/llms.txt

Use this file to discover all available pages before exploring further.

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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.

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Base URL

All endpoints are served under: 
https://api.eka.care/med-link/

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Authentication

Every request requires a Bearer access token: 
Authorization: Bearer <access_token>
Generate the token using the Eka authorization flow — see Authorization.

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Supported ontologies

OntologyontologyversionUse it formetadata
SNOMED CTsnomed20250401_extendedSymptoms, findings, disorders, proceduresNot used
LOINCloincv1.0Lab tests and observationsRecommended
Medicationmedicationv5.0Branded and generic drugsOptional
ICD-10-CM (Comprehend)icd-10-cmcomprehendDiagnoses from natural-language clinical textNot used
Always call List Registry to confirm the live ontology and version values before linking.

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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.

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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.

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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