Pipelines overview
EDS-NLP provides easy-to-use spaCy components.
| Pipeline | Description |
|---|---|
eds.normalizer |
Non-destructive input text normalisation |
eds.sentences |
Better sentence boundary detection |
eds.matcher |
A simple yet powerful entity extractor |
eds.terminology |
A simple yet powerful terminology matcher |
eds.contextual-matcher |
A conditional entity extractor |
eds.endlines |
An unsupervised model to classify each end line |
| Pipeline | Description |
|---|---|
eds.negation |
Rule-based negation detection |
eds.family |
Rule-based family context detection |
eds.hypothesis |
Rule-based speculation detection |
eds.reported_speech |
Rule-based reported speech detection |
eds.history |
Rule-based medical history detection |
| Pipeline | Description |
|---|---|
eds.dates |
Date extraction and normalisation |
eds.consultation_dates |
Identify consultation dates |
eds.measurements |
Measure extraction and normalisation |
eds.sections |
Section detection |
eds.reason |
Rule-based hospitalisation reason detection |
eds.tables |
Tables detection |
| Pipeline | Description |
|---|---|
eds.covid |
A COVID mentions detector |
eds.charlson |
A Charlson score extractor |
eds.elstonellis |
An Elston & Ellis code extractor |
eds.emergency.priority |
A priority score extractor |
eds.emergency.ccmu |
A CCMU score extractor |
eds.emergency.gemsa |
A GEMSA score extractor |
eds.sofa |
A SOFA score extractor |
eds.TNM |
A TNM score extractor |
eds.adicap |
A ADICAP codes extractor |
eds.drugs |
A drug mentions extractor |
eds.cim10 |
A CIM10 terminology matcher |
eds.umls |
An UMLS terminology matcher |
eds.CKD |
CKD extractor |
eds.COPD |
COPD extractor |
eds.cerebrovascular_accident |
Cerebrovascular accident extractor |
eds.congestive_heart_failure |
Congestive heart failure extractor |
eds.connective_tissue_disease |
Connective tissue disease extractor |
eds.dementia |
Dementia extractor |
eds.diabetes |
Diabetes extractor |
eds.hemiplegia |
Hemiplegia extractor |
eds.leukemia |
Leukemia extractor |
eds.liver_disease |
Liver disease extractor |
eds.lymphoma |
Lymphoma extractor |
eds.myocardial_infarction |
Myocardial infarction extractor |
eds.peptic_ulcer_disease |
Peptic ulcer disease extractor |
eds.peripheral_vascular_disease |
Peripheral vascular disease extractor |
eds.solid_tumor |
Solid tumor extractor |
eds.alcohol |
Alcohol consumption extractor |
eds.tobacco |
Tobacco consumption extractor |
| Pipeline | Description |
|---|---|
eds.nested-ner |
A trainable component for nested (and classic) NER |
eds.span-qualifier |
A trainable component for multi-class multi-label span qualification |
You can add them to your spaCy pipeline by simply calling add_pipe, for instance:
# ↑ Omitted code that defines the nlp object ↑
nlp.add_pipe("eds.normalizer")