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README.md

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-license: mit
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+---
+language: "en"
+tags:
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+license: mit
+---
+
+# Datasets used to test hospitalization prediction models
+
+Datasets used in testing the trained models presented in the paper ["Predicting Hospitalization with LLMs from  Health Insurance Data"](https://link.springer.com/article/10.1007/s11517-024-03251-4). We provide data in English and Portuguese. 
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+All data here is anonymized and represents the patient's event history, ordered from left to right in a sentence format, with data on the left being oldest and data on the right being newest. Label values 0 indicate that the patient was not hospitalized after that historical sequence, and 1 otherwise.
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+The original data is in Portuguese and was translated into English using the [translation-pt-en-t5](https://arxiv.org/abs/2008.08769v1) translation model. The data were randomly selected 5 times using the seeds [12, 23, 34, 45, 56] for each selection. Therefore, for each of the versions, Portuguese and English, there are 5 test sets.
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+Dataset with the suffix "pt" is in Portuguese and with the suffix "en" in English.
+
+## Test models
+
+To test the models, use the guidelines as described in the paper ["Predicting Hospitalization with LLMs from  Health Insurance Data"](https://link.springer.com/article/10.1007/s11517-024-03251-4). To carry out tests with RandomForest it is necessary to extract the embeddings using the [sentence transformers framework](https://www.sbert.net/).
+
+
+## More Information
+
+Refer to the original paper, [Predicting Hospitalization with LLMs from  Health Insurance Data](https://link.springer.com/article/10.1007/s11517-024-03251-4)
+
+Refert to another article related to this research, [Predicting Hospitalization from Health Insurance Data](https://ieeexplore.ieee.org/document/9945601)
+
+## Questions?
+
+Email:
+  - Everton F. Baro:  [email protected], [email protected]
+  - Luiz S. Oliveira: [email protected]
+  - Alceu de Souza Britto Junior: [email protected]