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Anosmia

Description

Application to extract and classify mentions related to anosmia.

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

The output includes- Positive mentions include:

“Loss of enjoyment of food due to anosmia”, “COVID symptoms such as anosmia”

Excludes Negative and Unknown mentions, e.g.:

“Nil anosmia”, “Doctor mentioned they had anosmia so could not smell patient”, “Anosmia related to people other than the patient”,

Unknown mentions: Annotations are coded as unknown when it is not clear if the patient has symptoms/experiences of anosmia. E.g.

“Mentions of medications for it” “Don’t come to the practice if you have any covid symptoms such as anosmia” etc. Definitions: Search term(case insensitive): Anosmia*

Results/Insights

Cohen's k = 83% (100 Random Documents). Instance level, (testing done on 100 random documents):Precision (specificity / accuracy) = 83% Recall (sensitivity / coverage) = 93%
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