---
language: "en"
tags:
- fill-mask
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. 

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.

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.

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:  efbaro@inf.ufpr.br, everton.barros@ifpr.edu.br
  - Luiz S. Oliveira: luiz.oliveira@ufpr.br
  - Alceu de Souza Britto Junior: alceu.junior@pucpr.br