Inteligência artificial no diagnóstico psiquiátrico: desafios e oportunidades na era do aprendizado de máquina
DOI:
https://doi.org/10.25118/2763-9037.2024.v14.1318Palavras-chave:
inteligência artificial, diagnóstico psiquiátrico, aprendizado de máquina, tecnologia de saúde mental, psiquiatria personalizadaResumo
A integração da inteligência artificial (IA) no diagnóstico psiquiátrico anuncia uma nova era nos cuidados de saúde mental, oferecendo oportunidades sem precedentes para melhorar a precisão do diagnóstico, personalizar o tratamento e agilizar os fluxos de trabalho clínicos. Uma abordagem sistemática foi utilizada, aderindo às diretrizes PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). Esta revisão da literatura explora o estado atual da IA no diagnóstico psiquiátrico, destacando tecnologias-chave como aprendizado de máquina, processamento de linguagem natural e aprendizado profundo. Discutimos a aplicação dessas tecnologias em vários transtornos psiquiátricos, incluindo depressão, ansiedade e esquizofrenia. Embora a IA seja imensamente promissora, permanecem desafios significativos, incluindo questões de privacidade de dados, preconceitos de modelo e validação clínica de ferramentas de IA. Além disso, considerações éticas e regulamentares devem ser abordadas para garantir uma implementação responsável. Esta revisão também examina as possíveis direções futuras da IA na psiquiatria, enfatizando a importância da colaboração entre os sistemas de IA e os médicos humanos. À medida que o campo evolui, a IA tem o potencial de transformar a prática psiquiátrica, oferecendo novos caminhos para a detecção precoce, cuidados personalizados e monitorização terapêutica.
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