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Title: Benchmarking the BRATECA Clinical Data Collection for Prediction Tasks
Authors: Consoli, Bernardo
Vieira, Renata
Bordin, Rafael
Issue Date: Feb-2023
Publisher: ScitePress
Citation: Consoli, B., Vieira, R. and Bordini, R. 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) - Volume 5: HEALTHINF, pages 338-345 ISBN: 978-989-758-631-6; ISSN: 2184-4305. DOI: 10.5220/0011671400003414
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 worth- while 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 architec- tures 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.
Type: article
Appears in Collections:CIDEHUS - Artigos em Livros de Actas/Proceedings

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