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GOPAD-Datasus/KDMiLe-Prediction

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KDMiLe Prediction

Paper

This repository is based on our paper:
Prediction of Infant Mortality in Brazil using Machine Learning and Entity Matching on Brazilian Unified Health System's Data
Authors: Morsoleto, R. et al.
Presented and accepted at: KDMiLe 2025.

Installation & Usage

Important

The input files weren't included in this repository due to their size. Both can be acquired from etlSUS and be manually loaded on to the data/input folder.

Poetry was used for dependency management. To download it, visit: python-poetry.org.

Activate a virtual environment and execute:

poetry install
# Or
pip install .
python main.py

License

LGNU | © GOPAD 2025

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Infant Mortality prediction based on the merge of SINASC and SIM databases through Entity Matching techniques.

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