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These features were used in our previous project for medication name detection in clinical notes and showed excellent performance.
Since the attribute linkage process only linked the attributes to the identified medication names, it did not influence the recall of medication name detection (i.e. recall = 100%).
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Medication entity detection, including medication name and attribute detection, was designed in-house based on the MALLET conditional random field (CRF) package [ 35, 36].
The medication cart can be filled using an automated system or a manual method and when using a manual method the medication can be arranged either by round time or by medication name.
A minority of study participants had missing data due to inability to recall medication name or frequency.
The medication name matching achieved 97.5% F-value on matched medications and 85.5% on discrepant medications.
Where medication name was unavailable, imputations were based on overall medication cost data.
Study staff entered prescription medications into the study database by medication name, but specific medication dosage was not entered.
The messages comprised varying content such as visitation date, hospital name, medication name, dosing frequency, dose, and administration methods.
Self-reported use of medication (name, frequency, and duration of medication use) is determined using a questionnaire [ 39].
No medication name was mentioned, but the features of the medication (effectiveness and side effects) resembled statins.
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