ehr-relation-extraction
importedsoftware/ehr-relation-extraction
NER and Relation Extraction from Electronic Health Records (EHR).
Machine-generated from the listed sources and not yet reviewed by a human.
- Category
- Software & Systems
- Subcategory
- unknown
- License
- MIT(osi)
- Status
- dormant
- Maturity
- deployed
- Organization
- unknown
- Country
- unknown
- Homepage
- ehr-info.ml
- Documentation
- unknown
- Tags
- adverse-drug-events · bert-relation-extraction · bilstm-crf · biobert · ehr · ehr-records · n2c2 · named-entity-recognition
- Regulatory
- unknown
Top contributors by commit count, from the project’s public repository. Avatars are served by their origin, not stored here. To be removed from this list, open an issue.
Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.
- MEMEehr · ehr-records
[npj Digital Medicine 2025] Multiple Embedding Model for EHR (MEME) used for strong prediction on Emergency Department tasks
- dose_instruction_parsernamed-entity-recognition
Parsing prescription dose instructions using Named Entity Recognition and rules
- healthseanamed-entity-recognition
Healthsea is a spaCy pipeline for analyzing user reviews of supplementary products for their effects on health.
- PICO_Parsernamed-entity-recognition
A clinical BERT-based NLP tool for parsing clinical trial abstracts following the PICO framework
- codelist-toolsehr-records
This is a set of useful tools for using, creating, validating and generally working with Codelists in Health Research. The tools are in Rust with Python and R bindings so they can be used in any of…
- Feline-Projectnamed-entity-recognition
Domain-adaptive NLP pipeline for feline veterinary NER using BERT
- api.github.com/repos/smitkiri/ehr-relation-extractionretrieved 2026-08-05 · via github-api
Machine-imported from GitHub search. Last push 2022-03-16, 90 stars, license reported as MIT. Category and schematic were assigned by keyword heuristics and are unreviewed.
Not yet verified by a human. Correct this record →
/v1/entries/49.json→ .entries["ehr-relation-extraction"]
Entries are sharded 64 ways by a stable hash of the id, so a consumer can find any record without an index.