Aplicaciones de modelos de lenguaje de gran tamaño en el tratamiento de la depresión: una revisión sistemática

Autores/as

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

DOI:

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

Palabras clave:

Salud Mental, Depresión, Modelos de Lenguaje de Gran Escala

Resumen

Objetivo: Este estudio revisa el uso de Modelos de Lenguaje de Gran Escala (LLMs) en el campo de la salud mental, enfocándose específicamente en el tratamiento de la depresión. Método: Se analizaron 18 artículos de un total inicial de 121, explorando cómo los LLMs ayudan en la toma de decisiones clínicas y en la interacción entre profesionales de la salud mental y pacientes deprimidos. Resultados: Los hallazgos principales muestran que los LLMs pueden aumentar la precisión en la detección de síntomas y mejorar las intervenciones terapéuticas a través de interfaces conversacionales avanzadas. Conclusión: El resumen destaca lagunas en la investigación existente y resalta la contribución del estudio para una mejor comprensión de la aplicabilidad de los LLMs en contextos clínicos.

Biografía del autor/a

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.

Citas

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Publicado

2024-11-19

Cómo citar

Lima, M. R., Ferreira, D. J., & Dias, E. S. (2024). Aplicaciones de modelos de lenguaje de gran tamaño en el tratamiento de la depresión: una revisión sistemática. Journal of Health Informatics, 16(Especial). https://doi.org/10.59681/2175-4411.v16.iEspecial.2024.1318

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