A server providing access to standardized medical terminologies and ontologies for clinical data interoperability.
API Access
Est. Price
~$15,000/yr est.
Update Frequency
On-demand
Pricing Tiers
1
Regions
1
Quality SignalsB
Freshness
Recently enriched
Complete
75%
API
API Available
Product Intelligence
Value Score
41
quality per $
Coverage
55
geo × freq × depth
Try-ability
0
ease of trial
Product Details
Use Cases
clinical data mappinginteroperabilitymedical codingEHR integration
Coverage
Global
Delivery
AWS MarketplaceAPI
Detected Use Cases
healthcare pharma
Pricing Tiers
Vedex estimate
~$15,000/yr est.
SUBSCRIPTIONMEDIUM
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Get an instant price estimate based on your organization profile — seats, usage rights, and contract term.Estimated ~$15,000/yr est.
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Web Authority
Notable10 mentions·1 platform
LinkedIn
10 × 2 pts+20
Evidence5 sources
LinkedIn
John Snow Labs' Medical Terminology Server on AWS
New Release! John Snow Labs' Medical Terminology Server is now available on the #AWS Marketplace: * UI & API for both exact and #AI-based ...
LinkedIn
Medical Terminology Server Simplifies Coding with LLM
... medical terminology server, built to bring order to that chaos. It combines healthcare-specific language models with FHIR concepts like value sets and ...
LinkedIn
LLM-enabled Medical Terminology Server by Kate Weber
Today! An LLM-enabled Medical Terminology Server” webinar on Wednesday, February 26th @ 2 pm ET, presented by Kate Weber of John Snow Labs.
Data Dictionary
Expected fields and columns in this data product
About Medical Terminology Server
Medical Terminology Server is an alternative data product offered by John Snow Labs, available on discovery. Data is updated on-demand. API access is available for programmatic integration. Vedex estimates pricing at roughly $15,000/yr (an estimate, not a vendor-published price).
A server providing access to standardized medical terminologies and ontologies for clinical data interoperability.
About John Snow Labs
John Snow Labs is a data provider vendor based in Wilmington, Delaware, USA. The model is a powerful tool for extracting SDoH entities from clinical text. It was specifically trained to identify the conditions in which people are born, grow, live, work, and age that impacts th...