ADL Score[source]

The eds.adl_score component extracts the adl score (Activities of Daily Life) score.

Examples

import edsnlp, edsnlp.pipes as eds

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

text = """
ADL 6/6.
"""

doc = nlp(text)
doc.ents
# Out: (ADL 6/6,)

Extensions

Each extraction exposes 2 extensions:

ent = doc.ents[0]

ent._.adl_score
# Out: 6.0

ent._.functional_status
# Out: 'healthy'

Parameters

PARAMETER	DESCRIPTION
`nlp`	The pipeline object TYPE: `PipelineProtocol`
`name`	Name of the component TYPE: `Optional[str]` DEFAULT: `'adl_score'`
`patterns`	A list of regexes to identify the score TYPE: `List[str]` DEFAULT: `default_patterns`
`attr`	Whether to match on the text ('TEXT') or on the normalized text ('NORM') TYPE: `str` DEFAULT: `'NORM'`
`score_normalization`	Function that takes the "raw" value extracted from the `value_extract` regex and should return: None if no score could be extracted The desired score value else TYPE: `Union[str, Callable[[Union[str, None]], Any]]` DEFAULT: `make_find_value_and_reference(admissible_references=[6], default_reference=6)`
`label`	Label name to use for the `Span` object and the extension TYPE: `str` DEFAULT: `'adl_score'`
`span_setter`	How to set matches on the doc TYPE: `SpanSetterArg` DEFAULT: `{'ents': True, 'adl_score': True, 'functional_status': True}`
`domain`	The frailty domain the score is related to TYPE: `str`
`severity_assigner`	Function that takes the score value and assigns the corresponding severity for the domain. TYPE: `Callable[[Span], Any]` DEFAULT: `adl_severity_assigner`

RETURNS	DESCRIPTION
`SimpleScoreMatcher`