Extract oncological entities and relations
This model extracts more than 40 oncology-related entities, including therapies, tests, staging, histological type, etc.
API AccessPAID
Est. Price
~$15,000/yr est.
Update Frequency
On-demand
Pricing Tiers
1
Regions
—
Quality SignalsB
Freshness
Recently enriched
Complete
75%
API
API Available
Product Overview
Healthcare NLP & Clinical Data Platform$
Offering: A comprehensive suite of NLP-based clinical entity recognition models and structured healthcare datasets for pharmacovigilance, clinical research, and population health analytics.
Best for: Healthcare data scientists and clinical researchers building automated pipelines for medical record de-identification and drug safety monitoring.
Benefits
- Extensive library of pre-trained clinical NLP models
- Multi-language support for clinical de-identification
- High-granularity SDoH and clinical entity extraction
- Cost-effective pricing compared to enterprise-scale healthcare data platforms
Drawbacks
⚠ Limited longitudinal patient journey tracking compared to Komodo Health · ⚠ Requires technical integration via API rather than turnkey dashboard solutionsProduct Intelligence
Value Score
31
quality per $
Coverage
15
geo × freq × depth
Try-ability
15
ease of trial
Product Details
Use Cases
Clinical trial patient matching | Oncology research and development | Real-world evidence generation | Cancer registry automation | Precision medicine program support | Clinical decision support systems | Population health management
Delivery
API
Data Sources
proprietary models
Detected Use Cases
healthcare pharma
Pricing Tiers
Vedex estimate
~$15,000/yr est.
PAIDMEDIUM
Add to Data Room
Get an instant price estimate based on your organization profile — seats, usage rights, and contract term.Estimated ~$15,000/yr est.
Request a sample directly from John Snow Labs.
Web Authority
High Authority10 mentions·4 platforms
Academic Papers
6 × 8 pts+48
LinkedIn
2 × 2 pts+4
Reddit
1 × 3 pts+3
Blogs & Newsletters
1 × 2 pts+2
Evidence5 sources
Academic Papers
Towards Scalable and Cross-Lingual Specialist Language ...
by M Rohanian · 2025 · Cited by 2 — We validated our models on oncology datasets, demonstrating strong results in named entity recognition, relation extraction, and document ...
Academic Papers
HARMON-E : Hierarchical Agentic Reasoning for Multi- ...
By adopting a hierarchical, agentic approach, we mitigate common pitfalls in extracting complex, interdependent oncology data and achieve end-to ...
Academic Papers
[1904.02347] Document-Level $N$-ary Relation Extraction ...
by R Jia · 2019 · Cited by 226 — In this paper, we propose a novel multiscale neural architecture for document-level n-ary relation extraction.
Data Dictionary
Expected fields and columns in this data product
About Extract oncological entities and relations
Extract oncological entities and relations is an alternative data product offered by John Snow Labs, available on databricks_marketplace. 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).
This model extracts more than 40 oncology-related entities, including therapies, tests, staging, histological type, etc.
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...