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Circumstantiality

Description

Application to identify instances of circumstantiality

Development approach: Machine-learning. Classification of past or present symptom: Both. Classes produced: Positive

The output includes- Positive mentions include:

“loose associations and circumstantiality”,

“circumstantial in nature”, “some circumstantiality at points”, “speech is less circumstantial”

Exclude Negative mentions:

“no signs of circumstantiality”, “no evidence of circumstantial”

Exclude Unknown mentions:

“Such as a hypothetical cause of something else” Definition: Search term(s): circumstan

Results/Insights

Cohen's k = 100% (50 annotated documents - 25 events/25 attachments). Instance level, i.e. for all specific mentions (testing done on 100 random documents): Precision (specificity / accuracy) = 94% Recall (sensitivity / coverage) = 92% Patient level – Testing done on 30 random document, one document per patient. Precision (specificity / accuracy) = 90%