Palavras-chave
Medicina
Machine Learning
Ética Médica
Diagnóstico por Imagem
Resumo
A inteligência artificial (IA) tem emergido como uma tecnologia transformadora na medicina contemporânea, promovendo avanços significativos no diagnóstico, tratamento e gestão da saúde. Esta revisão integrativa da literatura teve como objetivo analisar as aplicações clínicas da IA na medicina, seus benefícios, limitações e desafios éticos. A pesquisa foi conduzida nas bases de dados PubMed, Scopus, Web of Science, Embase, SciELO e Biblioteca Virtual em Saúde, utilizando descritores DeCS/MeSH, abrangendo o período de 2021 a 2026. Foram incluídos 100 artigos que atenderam aos critérios de elegibilidade. Os resultados demonstram que a IA, especialmente por meio de machine learning e deep learning, tem revolucionado o diagnóstico por imagem em radiologia, dermatologia, cardiologia e oncologia, com acurácia comparável ou superior à de especialistas humanos em diversos cenários. Modelos de linguagem de grande porte, como o ChatGPT, apresentam potencial para auxiliar na educação médica, suporte à decisão clínica e telemedicina. No entanto, limitações técnicas, como a dependência de dados de treinamento de qualidade, o problema do viés algorítmico e a falta de explicabilidade dos modelos, representam barreiras significativas. Desafios éticos relacionados à privacidade de dados, responsabilidade médica, consentimento informado e equidade no acesso também foram identificados. Conclui-se que, embora a IA ofereça imensas oportunidades para a medicina, sua implementação responsável requer governança robusta, regulamentação adequada e uma abordagem centrada no paciente que preserve a relação médico-paciente e os princípios bioéticos.
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Copyright (c) 2026 Maria Luiza Furtado Cutrim de Carvalho, Maria Clara Figueiredo Guimarães, Lucas Rosendo (Autor)