Application to identify instances of anergia.

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

The output includes-

Examples of positive mentions:

“feelings of anergia…”

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

“no anergia”,

“no evidence of anergia”,

“no feeling of anergia”.

Search term(case insensitive): anergia

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

Precision (specificity / accuracy) = 95% Recall (sensitivity / coverage) = 89% Patient level – All patients with primary diagnosis code F32 or F33 (testing done on 30 random document, one document per patient): Precision (specificity / accuracy) = 93%