Evaluation of machine learning models for the classification of breast cancer hormone receptors using micro-FTIR images
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2021
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SBFOTON INTERNATIONAL OPTICS AND PHOTONICS CONFERENCE
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Resumo
The breast cancer is the most incident cancer in
women. Evaluation of hormone receptors expression plays an
important role to outline treatment strategies. FTIR
spectroscopy imaging may be employed as an additional
technique, providing extra information to help physicians. In
this work, estrogen and progesterone receptors expression were
evaluated using tumors biopsies from human cell lines
inoculated in mice. FTIR images were collect from histological
sections, and six machine learning models were applied and
assessed. Xtreme gradient boost and Linear Discriminant
Analysis presented the best accuracies results, indicating to be
potential models for breast cancer classification tasks.
Como referenciar
VALLE, MATHEUS del; SANTOS, MOISES O. dos; SANTOS, SOFIA N. dos; BERNARDES, EMERSON S.; ZEZELL, DENISE M. Evaluation of machine learning models for the classification of breast cancer hormone receptors using micro-FTIR images. In: SBFOTON INTERNATIONAL OPTICS AND PHOTONICS CONFERENCE, May 31 - June 2, 2021, Online. Proceedings... Piscataway, NJ, USA: IEEE, 2021. DOI: 10.1109/SBFOTONIOPC50774.2021.9461946. Disponível em: http://repositorio.ipen.br/handle/123456789/32334. Acesso em: 30 Dec 2025.
Esta referência é gerada automaticamente de acordo com as normas do estilo IPEN/SP (ABNT NBR 6023) e recomenda-se uma verificação final e ajustes caso necessário.