Inteligência artificial aplicada à análise de imagens histológicas para apoio ao diagnóstico: uma revisão sistemática da evidência 2025-2026
Palavras-chave:
Inteligência artificial; histopatologia; diagnóstico; aprendizado profundo; revisão sistemática.Resumo
A inteligência artificial (IA) aplicada a imagens histológicas digitalizadas evoluiu rapidamente para tarefas diagnósticas complexas. Sintetizar as evidências publicadas entre 2025 e 2026 sobre aplicações de IA em histopatologia diagnóstica. Revisão sistemática segundo PRISMA 2020 nas bases PubMed, Google Acadêmico e ScienceDirect, incluindo estudos originais em humanos com imagens histológicas digitalizadas para diagnóstico, classificação ou estratificação clínica. Foram incluídos 22 estudos, com predomínio de patologia oncológica (trato gastrointestinal, mama, sistema nervoso central). As arquiteturas de IA evoluíram de redes neurais convolucionais para aprendizado multi-instância, transformers e foundation models. Mais da metade reportou validação externa. As principais métricas foram AUROC, acurácia e índices de concordância. A IA em patologia digital mostra crescente sofisticação, mas persiste heterogeneidade metodológica que limita sua implementação clínica generalizada.
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