DETECÇÃO E CLASSIFICAÇÃO DE LESÕES MAMÁRIAS EM IMAGENS BIOMÉDICAS DE FORMA EXPLICÁVEL
DOI:
https://doi.org/10.56238/arev7n9-289Palavras-chave:
Lesões Mamárias, Câncer de Mama, Imagem Biomédica, Aprendizado de MáquinaResumo
Objetivo: O câncer de mama é um importante problema de saúde pública e a principal causa de morte por câncer entre mulheres adultas no Brasil. O diagnóstico tardio contribui para altas taxas de mortalidade e cirurgias invasivas. O acesso limitado a exames de imagem resulta em diagnósticos em estágios avançados, reforçando a necessidade de detecção precoce para aumentar as taxas de cura e evitar procedimentos agressivos. O objetivo deste estudo é aprimorar o diagnóstico do câncer de mama, particularmente em países com diagnóstico tardio prevalente, aplicando inteligência artificial avançada e técnicas de aprendizado extremo a imagens termográficas.
Métodos: O estudo utiliza inteligência artificial avançada (IA) e técnicas de aprendizado extremo para analisar imagens termográficas. O objetivo é desenvolver um sistema computacional que não apenas diagnostique o câncer de mama com precisão, mas também forneça explicações para suas decisões de forma compreensível para os profissionais de saúde.
Resultados: A abordagem de IA proposta demonstrou eficiência na detecção e classificação de lesões mamárias em imagens termográficas. O sistema alcançou uma acurácia de 89,70% na distinção de lesões malignas de outros diagnósticos em seu melhor cenário.
Conclusão: O sistema desenvolvido representa um avanço significativo no diagnóstico do câncer de mama, particularmente em regiões onde diagnósticos em estágio avançado são comuns. Ele tem potencial para melhorar a precisão diagnóstica, contribuir para melhores resultados para os pacientes e aumentar as perspectivas de recuperação de pacientes com câncer de mama.
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