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edsnlp.pipes.ner.frailty.sensory_status.factory

create_component = registry.factory.register('eds.sensory_status', assigns=['doc.ents', 'doc.spans'])(SensoryMatcher) module-attribute [source]

The eds.sensory_status pipeline component extracts mentions of the sensory status.

Details of the used patterns 
# fmt: off
from ..utils import make_status_assign, normalize_space_characters

healthy = dict(
    source="healthy",
    regex=[r"acuite (?:visuelle|auditive) normale"],
    regex_attr="NORM",
)
severe = dict(
    source="severe",
    regex=[
        r"\bcecite\b",
        "aveugle",
        "surdite",
    ],
    regex_attr="NORM",
)
altered = dict(
    source="altered",
    regex=[
        r"appareillages? auditifs?",
        "lunettes",
        r"baisse d'acuite visuelle",
    ],
    regex_attr="NORM",
)
mild = dict(
    source="mild",
    regex=[
        "hypoacousie",
        "presbyacousie",
        "difficultes? visuelles?",
    ],
    regex_attr="NORM",
)
assourdi = dict(
    source="severe_assourdi",
    regex=[
        r"sourde?",
    ],
    exclude=dict(regex=[r"coeurs?", r"cardiaques?"], window=-3),
    regex_attr="NORM",
)
bav = dict(
    source="altered_bav",
    regex=[r"\bBAV\b"],
    exclude=dict(
        regex=[
            "pacemaker",
            "coeur",
            r"cardiaques",
            "complet",
            "nephrologue",
            "cardiologue",
            "degre",
        ],
        window=(-15, 10),
        regex_attr="NORM",
    ),
    regex_attr="ORTH",
)
other = dict(
    source="other",
    regex=[
        r"bilan ophtalmo(?:logique)?",
        "avis ophtalmologique",
        "examen ophtalmologique",
    ],
    regex_attr="NORM",
)

status = dict(
    source="other_status",
    regex=[
        "statut visuel",
        "etat visuel",
        "statut auditif",
        "etat auditif",
        "statut sensoriel",
        "etat sensoriel",
    ],
    regex_attr="NORM",
    assign=make_status_assign(),
)

default_patterns = normalize_space_characters(
    [
        other,
        healthy,
        altered,
        mild,
        severe,
        assourdi,
        bav,
        status,
    ]
)

# fmt: on

Extensions

On each span span that match, the following attribute is available:

  • span._.sensory_status: set to None.

It will specify the severity of the mention regarding the sensory status of the patient.

Possible values are:

  • healthy : this span suggests the patient is well regarding that domain.
  • altered_nondescript : this span suggests the patient is not well, but it is not yet possible to ascertain the degree of alteration.
  • altered_mild : this span suggests a light alteration regarding this domain.
  • altered_severe : this span suggests a severe alteration regarding this domain.
  • other : this span is not indicative of the level of alteration regarding this domain. Still, it hints that this domain has been evaluated.

Examples

import edsnlp, edsnlp.pipes as eds

nlp = edsnlp.blank("eds")
nlp.add_pipe(eds.sentences())
nlp.add_pipe(eds.normalizer())
nlp.add_pipe(f"eds.sensory_status")

Below are a few examples:

Parameters

PARAMETER DESCRIPTION
nlp

The pipeline

TYPE: Optional[PipelineProtocol]

name

The name of the component

TYPE: Optional[str] DEFAULT: sensory_status

patterns

The patterns to use for matching

TYPE: FullConfig DEFAULT: [{'source': 'other', 'regex': ['bilan\\s{1,3}op...

label

The label to use for the Span object and the extension

TYPE: str DEFAULT: sensory_status

span_setter

How to set matches on the doc

TYPE: SpanSetterArg DEFAULT: {'ents': True, 'sensory_status': True}