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Enhancing tertiary cardiology triage with vectorcardiographic features: a machine learning approach using real-world data

Published Print: 2026-01

Authors

da Costa, Lucas José https://orcid.org/0009-0006-1169-3772
Ruiz Uemoto, Vinicius https://orcid.org/0000-0002-9629-4298
FN de Marchi, Mariana https://orcid.org/0000-0002-6738-0322
de Aguiar Hortegal, Renato https://orcid.org/0000-0003-0031-335X
Valeri de Freitas, Renata https://orcid.org/0000-0001-5029-6231
Funding

Funding for this research was provided by:

Fundação de Amparo à Pesquisa do Estado de São Paulo (2021/07005\u20134)
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Text and Data Mining valid from 2026-01-01

Text and Data Mining valid from 2026-01-01

Version of Record valid from 2025-12-18
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This article is maintained by: Elsevier

Article Title: Enhancing tertiary cardiology triage with vectorcardiographic features: a machine learning approach using real-world data

Journal Title: Clinics

CrossRef DOI link to publisher maintained version: https://doi.org/10.1016/j.clinsp.2025.100856

Content Type: article

Copyright: © 2025 Published by Elsevier España, S.L.U. on behalf of HCFMUSP.

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