Application to identify instances of arousal excluding sexual arousal.

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

The output includes:

Positive mentions include:

“...the decisions she makes when emotionally aroused”, “...during hyperaroused state”, “following an incidence of physiological arousal”

Exclude Negative mentions include:

“mentions of sexual arousal”, “no arousal”, “not aroused”, “denies being aroused”

Unknown mentions include:

“annotations include unclear statements and hypotheticals” Definitions: Search term(s): arous

Cohen's k = 95% (50 un-annotated documents - 25 events/25 attachments, search term ‘arous’). Instance level, i.e. for all specific mentions (testing done on 100 random documents):

Precision (specificity / accuracy) = 89% Recall (sensitivity / coverage) = 91%