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Authors: Bernardo Consoli 1 ; Renata Vieira 2 and Rafael Bordini 1

Affiliations: 1 School of Technology, Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Brazil ; 2 CIDEHUS, University of Évora, Évora, Portugal

Keyword(s): Computational Medicine, Healthcare Informatics, Clinical Prediction, Clinical Data, BRATECA.

Abstract: Expanding the usability of location-specific clinical datasets is an important step toward expanding research into national medical issues, rather than only attempting to generalize hypotheses from foreign data. This means that benchmarking such datasets, thus proving their usefulness for certain kinds of research, is a worthwhile task. This paper presents the first results of widely used prediction tasks from data contained within the BRATECA collection, a Brazilian tertiary care data collection, and also results for neural network architectures using these newly created test sets. The architectures use both structured and unstructured data to achieve their results. The obtained results are expected to serve as benchmarks for future tests with more advanced models based on the data available in BRATECA.

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Paper citation in several formats:
Consoli, B.; Vieira, R. and Bordini, R. (2023). Benchmarking the BRATECA Clinical Data Collection for Prediction Tasks. In Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2023) - HEALTHINF; ISBN 978-989-758-631-6; ISSN 2184-4305, SciTePress, pages 338-345. DOI: 10.5220/0011671400003414

@conference{healthinf23,
author={Bernardo Consoli. and Renata Vieira. and Rafael Bordini.},
title={Benchmarking the BRATECA Clinical Data Collection for Prediction Tasks},
booktitle={Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2023) - HEALTHINF},
year={2023},
pages={338-345},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011671400003414},
isbn={978-989-758-631-6},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2023) - HEALTHINF
TI - Benchmarking the BRATECA Clinical Data Collection for Prediction Tasks
SN - 978-989-758-631-6
IS - 2184-4305
AU - Consoli, B.
AU - Vieira, R.
AU - Bordini, R.
PY - 2023
SP - 338
EP - 345
DO - 10.5220/0011671400003414
PB - SciTePress

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