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--- |
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annotations_creators: |
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- expert-generated |
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language: |
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- es |
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language_creators: |
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- expert-generated |
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license: |
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- afl-3.0 |
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multilinguality: |
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- monolingual |
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pretty_name: CARES |
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size_categories: |
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- 1K<n<10K |
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source_datasets: |
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- original |
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tags: |
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- radiology |
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- biomedicine |
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- ICD-10 |
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task_categories: |
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- text-classification |
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--- |
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# CARES - A Corpus of Anonymised Radiological Evidences in Spanish 📑🏥 |
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CARES is a high-quality text resource manually labeled with ICD-10 codes and reviewed by radiologists. These types of resources are essential for developing automatic text classification tools as they are necessary for training and fine-tuning our computational systems. |
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The CARES corpus has been manually annotated using the ICD-10 ontology, which stands for for the 10th version of the International Classification of Diseases. For each radiological report, a minimum of one code and a maximum of 9 codes were assigned, while the average number of codes per text is 2.15 with the standard deviation of 1.12. |
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The corpus was additionally preprocessed in order to make its format coherent with the automatic text classification task. Considering the hierarchical structure of the ICD-10 ontology, each sub-code was mapped to its respective code and chapter, obtaining two new sets of labels for each report. The entire CARES collection contains 6,907 sub-code annotations among the 3,219 radiologic reports. There are 223 unique ICD-10 sub-codes within the annotations, which were mapped to 156 unique ICD-10 codes and 16 unique chapters of the cited ontology. |
