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arXiv · 2412.03176

Automatic detection of diseases in Spanish clinical notes combining medical language models and ontologies

Leon-Paul Schaub Torre·Pelayo Quiros·Helena Garcia Mieres
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Abstract

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.

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Leon-Paul Schaub Torre, Pelayo Quiros, Helena Garcia Mieres. 2024-12-04. Automatic detection of diseases in Spanish clinical notes combining medical language models and ontologies. https://arxiv.org/abs/2412.03176

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