README.md

metadata

license: mit
task_categories:
  - token-classification
language:
  - en
tags:
  - biology
  - medical
size_categories:
  - 1M<n<10M
field:
  - data

MACCROBAT-biomedical-ner

Uses

import datasets
from datasets import load_dataset

features_data = datasets.Features(
    {
        "full_text": Value(dtype="string"),
        "ner_info": [
            {
                "text": Value(dtype="string"),
                "label": Value(dtype="string"),
                "start": Value(dtype="int64"),
                "end": Value(dtype="int64"),
            }
        ],
        "tokens": Sequence(Value(dtype="string")),
        "ner_labels": Sequence(
            ClassLabel(
                names=[
                    "O",
                    "B-ACTIVITY",
                    "I-ACTIVITY",
                    "I-ADMINISTRATION",
                    "B-ADMINISTRATION",
                    "B-AGE",
                    "I-AGE",
                    "I-AREA",
                    "B-AREA",
                    "B-BIOLOGICAL_ATTRIBUTE",
                    "I-BIOLOGICAL_ATTRIBUTE",
                    "I-BIOLOGICAL_STRUCTURE",
                    "B-BIOLOGICAL_STRUCTURE",
                    "B-CLINICAL_EVENT",
                    "I-CLINICAL_EVENT",
                    "B-COLOR",
                    "I-COLOR",
                    "I-COREFERENCE",
                    "B-COREFERENCE",
                    "B-DATE",
                    "I-DATE",
                    "I-DETAILED_DESCRIPTION",
                    "B-DETAILED_DESCRIPTION",
                    "I-DIAGNOSTIC_PROCEDURE",
                    "B-DIAGNOSTIC_PROCEDURE",
                    "I-DISEASE_DISORDER",
                    "B-DISEASE_DISORDER",
                    "B-DISTANCE",
                    "I-DISTANCE",
                    "B-DOSAGE",
                    "I-DOSAGE",
                    "I-DURATION",
                    "B-DURATION",
                    "I-FAMILY_HISTORY",
                    "B-FAMILY_HISTORY",
                    "B-FREQUENCY",
                    "I-FREQUENCY",
                    "I-HEIGHT",
                    "B-HEIGHT",
                    "B-HISTORY",
                    "I-HISTORY",
                    "I-LAB_VALUE",
                    "B-LAB_VALUE",
                    "I-MASS",
                    "B-MASS",
                    "I-MEDICATION",
                    "B-MEDICATION",
                    "I-NONBIOLOGICAL_LOCATION",
                    "B-NONBIOLOGICAL_LOCATION",
                    "I-OCCUPATION",
                    "B-OCCUPATION",
                    "B-OTHER_ENTITY",
                    "I-OTHER_ENTITY",
                    "B-OTHER_EVENT",
                    "I-OTHER_EVENT",
                    "I-OUTCOME",
                    "B-OUTCOME",
                    "I-PERSONAL_BACKGROUND",
                    "B-PERSONAL_BACKGROUND",
                    "B-QUALITATIVE_CONCEPT",
                    "I-QUALITATIVE_CONCEPT",
                    "I-QUANTITATIVE_CONCEPT",
                    "B-QUANTITATIVE_CONCEPT",
                    "B-SEVERITY",
                    "I-SEVERITY",
                    "B-SEX",
                    "I-SEX",
                    "B-SHAPE",
                    "I-SHAPE",
                    "B-SIGN_SYMPTOM",
                    "I-SIGN_SYMPTOM",
                    "B-SUBJECT",
                    "I-SUBJECT",
                    "B-TEXTURE",
                    "I-TEXTURE",
                    "B-THERAPEUTIC_PROCEDURE",
                    "I-THERAPEUTIC_PROCEDURE",
                    "I-TIME",
                    "B-TIME",
                    "B-VOLUME",
                    "I-VOLUME",
                    "I-WEIGHT",
                    "B-WEIGHT",
                ]
            )
        ),
    }
)
# load the data
medical_ner_data = load_dataset("singh-aditya/MACCROBAT-biomedical-ner", field="data", features=features_data)
print(medical_ner_data)

DatasetDict({
    train: Dataset({
        features: ['ner_labels', 'tokens', 'full_text', 'ner_info'],
        num_rows: 200
    })
})

Dataset Structure

[More Information Needed]

Dataset Creation

Data Collection and Processing

[More Information Needed]

BibTeX:

{
  article= Caufield2020,
  author = "J. Harry Caufield",
  title = "{MACCROBAT}",
  year = "2020",
  month = "1",
  url = "https://figshare.com/articles/dataset/MACCROBAT2018/9764942",
  doi = "10.6084/m9.figshare.9764942.v2"
}