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. Author manuscript; available in PMC: 2023 Sep 8.
Published in final edited form as: Proc (IEEE Int Conf Healthc Inform). 2022 Sep 8;2022:84–89. doi: 10.1109/ichi54592.2022.00024

Table III.

F1-scores of ProtoNER model. The results obtained according to each entity type of each dataset. the entity types with less than 10 instances and their performance have been highlighted in bold and underlined.

Datasets Labels Instances of label F1-score
N2C2 2018 Drug 12510 63.92
Strength 5519 83.45
Form 5398 87.93
Frequency 4062 63.57
Dosage 3280 75.12
Route 4672 85.72
Duration 461 0.00
Reason 2962 40.81
ADE 692 24.24
I2B2 2014 PATIENT 903 61.81
DOCTOR 1986 63.37
USERNAME 60 93.88
PROFESSION 161 66.67
HOSPITAL 945 55.03
ORGANIZATION 88 19.99
STREET 162 96.87
CITY 293 69.99
STATE 250 76.71
COUNTRY 61 85.71
ZIP 164 90.14
LOCATION-OTHER 4 0.00
AGE 874 79.99
DATE 5087 69.31
PHONE 175 81.97
FAX 5 0.00
EMAIL 2 0.00
URL 6 0.00
HEALTHPLAN 1 0.00
MEDICALRECORD 337 78.57
IDNUM 78 54.05
DEVICE 7 0.00
BIOID 1 0.00
MIMIC III CONDITION/SYMPTOM 2365 40.01
DRUG 690 65.24
AMOUNT 403 50.01
TIME 326 40.63
MEASUREMENT 665 49.85
LOCATION 618 47.31
EVENT 757 36.86
FREQUENCY 62 0.00
ORGANIZATION 114 28.62
DATE 2 0.00
AGE 44 95.25
GENDER 36 99.98
BioNLP 2016 GENE 18258 27.87
SMM4H 2021 ADE 1124 7.84