Liver disease[source]

The eds.liver_disease pipeline component extracts mentions of liver disease.

Details of the used patterns

# fmt: off
mild = dict(
    source="mild",
    regex=[
        r"cholangites?.{1,10}(sclero|secondaire)",
        r"fibrose.{1,10}(hepatique|foie)",
        r"hepatite.{1,15}chroni\w+",
        r"hepatopath\w+",
        r"\bnash\b",
        r"(maladie|sydrome?).{1,10}hanot",
        r"surinfections?.{1,5}delta",
        r"\bcbp\b",
        r"\bmaf\b",
    ],
    regex_attr="NORM",
    exclude=dict(
        regex="\bdots?\b",
        window=-5,
    ),
)

moderate_severe = dict(
    source="moderate_severe",
    regex=[
        r"cirr?hose",
        r"necrose.{1,10}(hepati|foie)",
        r"varice.{1,10}(estomac|oesopha|gastr)",
        r"\bvo\b.{1,5}(stade|grade).(1|2|3|i{1,3})",
        r"hypertension.{1,5}portale?",
        r"scleroses?.{1,5}hepato\s*portale?",
        r"sydrome?.{1,10}hepato.?ren",
        r"insuff?isance.{1,5}hepa",
        r"encephalopath\w+.{1,5}hepa",
        r"\btips\b",
    ],
    regex_attr="NORM",
)

transplant = dict(
    source="transplant",
    regex=[
        r"(?<!pre.?)(gref?fe|transplant).{1,12}(hepatique|foie)",
    ],
    regex_attr="NORM",
    exclude=dict(
        regex="chc",
        window=(-5, 5),
    ),
)

default_patterns = [
    mild,
    moderate_severe,
    transplant,
]

# fmt: on

Extensions

On each span span that match, the following attributes are available:

span._.detailed_status: set to either
- "MILD" for mild liver diseases
- "MODERATE_TO_SEVERE" else

Examples

import edsnlp, edsnlp.pipes as eds

nlp = edsnlp.blank("eds")
nlp.add_pipe(eds.sentences())
nlp.add_pipe(
    eds.normalizer(
        accents=True,
        lowercase=True,
        quotes=True,
        spaces=True,
        pollution=dict(
            information=True,
            bars=True,
            biology=True,
            doctors=True,
            web=True,
            coding=True,
            footer=True,
        ),
    ),
)
nlp.add_pipe(eds.liver_disease())

Below are a few examples:

1234

text = "Il y a une fibrose hépatique"
doc = nlp(text)
spans = doc.spans["liver_disease"]

spans
# Out: [fibrose hépatique]

text = "Une hépatite B chronique"
doc = nlp(text)
spans = doc.spans["liver_disease"]

spans
# Out: [hépatite B chronique]

text = "Le patient consulte pour une cirrhose"
doc = nlp(text)
spans = doc.spans["liver_disease"]

spans
# Out: [cirrhose]

span = spans[0]

span._.detailed_status
# Out: MODERATE_TO_SEVERE

text = "Greffe hépatique."
doc = nlp(text)
spans = doc.spans["liver_disease"]

spans
# Out: [Greffe hépatique]

span = spans[0]

span._.detailed_status
# Out: MODERATE_TO_SEVERE

Parameters

PARAMETER	DESCRIPTION
`nlp`	The pipeline TYPE: `Optional[PipelineProtocol]`
`name`	The name of the component TYPE: `Optional[str]`
`patterns`	The patterns to use for matching TYPE: `FullConfig` DEFAULT: `[{'source': 'mild', 'regex': ['cholangites?.{1,...`
`label`	The label to use for the `Span` object and the extension TYPE: `str` DEFAULT: `liver_disease`
`span_setter`	How to set matches on the doc TYPE: `SpanSetterArg` DEFAULT: `{'ents': True, 'liver_disease': True}`

Authors and citation

The eds.liver_disease component was developed by AP-HP's Data Science team with a team of medical experts, following the insights of the algorithm proposed by Petit-Jean et al., 2024.

Petit-Jean T., Gérardin C., Berthelot E., Chatellier G., Frank M., Tannier X., Kempf E. and Bey R., 2024. Collaborative and privacy-enhancing workflows on a clinical data warehouse: an example developing natural language processing pipelines to detect medical conditions. Journal of the American Medical Informatics Association. 31, pp.1280-1290. 10.1093/jamia/ocae069