Application to identify instances of anhedonia (inability to experience pleasure from activities usually found enjoyable).

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

The output includes-

Examples of positive mentions:

“ X had been anhedonic”,

“ X has anhedonia”.

Examples of negative / irrelevant mentions (not included in the output):

“no anhedonia”,

“not anhedonic”,

Used in a list, not applying to patient (e.g. typical symptoms include …);

Uncertain (might have anhedonia, ?anhedonia, possible anhedonia);

Search term(s): anhedon

Cohen's k=85% (50 un-annotated documents - 25 events/25 attachments, search term 'anhedon*’). Instance level, (testing done on 100 random documents):

Precision (specificity / accuracy) = 93% Recall (sensitivity / coverage) = 86% Patient level – All patients with primary diagnosis code F32 or F33 (testing done on 30 random document, one document per patient) Precision (specificity / accuracy) = 87%