Automatic detection of diseases in Spanish clinical notes combining medical language models and ontologies
| Autor: | Torre, Leon-Paul Schaub, Quiros, Pelayo, Mieres, Helena Garcia |
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| Rok vydání: | 2024 |
| Předmět: | |
| Druh dokumentu: | Working Paper |
| Popis: | In this paper we present a hybrid method for the automatic detection of dermatological pathologies in medical reports. We use a large language model combined with medical ontologies to predict, given a first appointment or follow-up medical report, the pathology a person may suffer from. The results show that teaching the model to learn the type, severity and location on the body of a dermatological pathology, as well as in which order it has to learn these three features, significantly increases its accuracy. The article presents the demonstration of state-of-the-art results for classification of medical texts with a precision of 0.84, micro and macro F1-score of 0.82 and 0.75, and makes both the method and the data set used available to the community. Comment: Translation of SEPLN 2024 es paper |
| Databáze: | arXiv |
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