ClinicalBERT
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A to Z
- A · App
- No
- B · Built By
- MIT
- C · CEO & Politics
- N/A (academic research) — No public partisan activity documented
- D · Date
- 2019
- E · Expertise
- Intermediate+
- F · Free Tier
- Yes
- G · Generates
- Text only
- H · Deployment
- Cloud + Local (open weights)
- I · Inputs
- Text
- J · Jurisdiction
- USA
- K · Key Staffers
- Kexin Huang (Lead author), Rajesh Ranganath (Senior author)
- L · Languages
- English-primary
- M · Model Type
- Medical NLP
- N · Safety Issues
- None reported
- O · Open Source
- Yes — open weights
- P · Pricing
- Free (open weights, MIT)
- Q · AIDb Rating
- [UNKNOWN]
- R · What Makes It Special
- ClinicalBERT, publicly released BERT models for clinical text, one for generic clinical notes and one for discharge summaries; its authors found they improved three common clinical NLP tasks over non-specific embeddings but did worse on two de-identification tasks.
- S · Stock / Status
- University
- T · Training Cutoff
- [UNKNOWN]
- U · Users
- [UNKNOWN]
- V · Voice Chat
- No
- W · Weights
- Downloadable
- X · X Handle
- [UNKNOWN]
- Y · Year Founded
- [UNKNOWN]
- Z · Bottom Line
- Open-weights Medical NLP from MIT, released 2019.
Data completeness 81% · Last verified 2026-05-12 · Primary source ↗
Cite this
“ClinicalBERT.” AIDb — The AI Database. Verified 2026-05-12. https://theaidatabase.com/m/clinicalbert.html