Explainable LightGBM approach for predicting myocardial infarction mortality (2023)
Fonte: Proceedings. Nome do evento: International Conference on Computational Science and Computational Intelligence - CSCI. Unidade: ICMC
Assuntos: APRENDIZADO COMPUTACIONAL, DIAGNÓSTICO POR COMPUTADOR, TECNOLOGIAS DA SAÚDE, INFARTO DO MIOCÁRDIO
ABNT
VICENTE, Ana Letícia Garcez e MALAQUIAS JUNIOR, Roseval Donisete e ROMERO, Roseli Aparecida Francelin. Explainable LightGBM approach for predicting myocardial infarction mortality. 2023, Anais.. Piscataway: IEEE, 2023. Disponível em: https://doi.org/10.1109/CSCI62032.2023.00057. Acesso em: 16 nov. 2024.APA
Vicente, A. L. G., Malaquias Junior, R. D., & Romero, R. A. F. (2023). Explainable LightGBM approach for predicting myocardial infarction mortality. In Proceedings. Piscataway: IEEE. doi:10.1109/CSCI62032.2023.00057NLM
Vicente ALG, Malaquias Junior RD, Romero RAF. Explainable LightGBM approach for predicting myocardial infarction mortality [Internet]. Proceedings. 2023 ;[citado 2024 nov. 16 ] Available from: https://doi.org/10.1109/CSCI62032.2023.00057Vancouver
Vicente ALG, Malaquias Junior RD, Romero RAF. Explainable LightGBM approach for predicting myocardial infarction mortality [Internet]. Proceedings. 2023 ;[citado 2024 nov. 16 ] Available from: https://doi.org/10.1109/CSCI62032.2023.00057