Inteligência artificial aplicada ao diagnóstico de câncer por exames de imagem
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Resumo
Objetivo: Revisar a aplicação da Inteligência Artificial (IA) no diagnóstico de câncer através de exames de imagem, analisando tendências e avanços recentes na intersecção entre IA e medicina diagnóstica. Métodos: Foi realizada uma pesquisa bibliográfica em bases de dados eletrônicas, selecionando artigos científicos, revisões sistemáticas e meta-análises publicados entre 2017 e 2023. Os estudos incluíram algoritmos de IA, técnicas de aprendizado de máquina e redes neurais aplicadas a exames de imagem para detecção, classificação e diagnóstico de câncer. Resultados: A análise focou em modelos de reconhecimento de imagem para diagnóstico de câncer, priorizando métricas de sensibilidade e especificidade. Foram destacados estudos que compararam o desempenho de radiologistas com sistemas de IA mostrando que em alguns casos a IA superou os profissionais e, em outros, melhorou significativamente o desempenho dos radiologistas quando usada como assistência. Considerações finais: A IA mostrou-se uma ferramenta promissora no diagnóstico de câncer por imagem. A combinação de IA com dados clínicos pode melhorar as métricas de diagnóstico. Limitações incluem a qualidade e quantidade de imagens para treinamento, mas novas tecnologias como IA Generativa estão surgindo para superar esses desafios.
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