Medication Regimen Extraction From Medical Conversations
Table 3: Performance (ROUGE-1 F1) breakdown of the best performing models measured on the 10% test dataset for the MR extraction task, refer Results section for more details. PT: using pretrained encoder; MD: Multi-decoder
['Models', 'Dosage None', 'Dosage MM', 'Dosage MN', 'Dosage NBM', 'Frequency None', 'Frequency NN']
We breakdown the Frequency extraction into two categories,: 1) None: ground truth Frequency tag is ‘none’, and 2) NN (Not None): ground truth Frequency tag is not ‘none’. Similarly, the Dosage extraction into 4 categories: 1) None: ground truth dosage tag is ‘none’, 2) MM (Multiple Medicine): input segment has more than one Medication mentioned, 3) MN (Multiple Numbers): input segment has more than one number present, and 4) NBM (Number between correct Dosage and Medicine) : between the Medication Name and the correct Dosage in the input segment there are other numbers present. Note that the categories of the Dosage extraction task are not exhaustive, and one tag can belong to multiple categories.