Aplicações de modelos de linguagem de grande escala no tratamento de depressão: uma revisão sistemática

Autores

  • Maurício Rodrigues Lima UFG
  • Deller James Ferreira UFG
  • Elisângela Silva Dias UFG

DOI:

https://doi.org/10.59681/2175-4411.v16.iEspecial.2024.1318

Palavras-chave:

Saúde Mental, Depressão, Modelos de Linguagem de Grande Escala

Resumo

Objetivo: Este estudo revisa o uso de Modelos de Linguagem de Grande Escala (LLMs) na área da saúde mental, focando especificamente no tratamento da depressão. Método: Foram analisados 18 artigos de um total inicial de 121, explorando como os LLMs auxiliam na tomada de decisões clínicas e na interação entre profissionais de saúde mental e pacientes deprimidos. Resultados: Os resultados principais mostram que os LLMs podem aumentar a precisão na detecção de sintomas e melhorar as intervenções terapêuticas por meio de interfaces conversacionais avançadas. Conclusão: O resumo aponta para lacunas na pesquisa existente e ressalta a contribuição do estudo para uma melhor compreensão da aplicabilidade dos LLMs em contextos clínicos.

Biografias Autor

Maurício Rodrigues Lima, UFG

Especialista em Engenharia de Software, Instituto de Informática, UFG, Goiânia (GO), Brasil.

Deller James Ferreira, UFG

Professora Dra, Instituto de Informática, UFG, Goiânia (GO), Brasil.

Elisângela Silva Dias, UFG

Professora Dra, Instituto de Informática, UFG, Goiânia (GO), Brasil.

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Publicado

2024-11-19

Como Citar

Lima, M. R., Ferreira, D. J., & Dias, E. S. (2024). Aplicações de modelos de linguagem de grande escala no tratamento de depressão: uma revisão sistemática. Journal of Health Informatics, 16(Especial). https://doi.org/10.59681/2175-4411.v16.iEspecial.2024.1318

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