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

Liu S, Zheng C, Demasi O, Sabour S, Li Y, Yu Z, Jiang Y, Huang M. Towards Emotional Support Dialog Systems. In: Zong C, Xia F, Li W, Navigli R, editors. Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers); 2021 Aug; Online. Association for Computational Linguistics; p. 3469–3483. Disponível em: https://aclanthology.org/2021.acl-long.269. DOI: 10.18653/v1/2021.acl-long.269. DOI: https://doi.org/10.18653/v1/2021.acl-long.269

Grové C. Co-developing a mental health and wellbeing chatbot with and for young people. Frontiers in Psychiatry. 2021;11. DOI: https://doi.org/10.3389/fpsyt.2020.606041

Demszky D, et al. Using large language models in psychology. Nature Reviews Psychology. 2023;2(11):688–701. DOI: https://doi.org/10.1038/s44159-023-00241-5

Siddaway AP, Wood A, Hedges L. How to do a systematic review: A best practice guide for conducting and reporting narrative reviews, meta-analyses, and meta-syntheses. Annual Review of Psychology. 2019;70:747-770. DOI: 10.1146/annurev-psych-010418-102803. DOI: https://doi.org/10.1146/annurev-psych-010418-102803

Carrera-Rivera A, et al. How-to conduct a systematic literature review: A quick guide for computer science research. MethodsX. 2022;9:101895. DOI: https://doi.org/10.1016/j.mex.2022.101895

Page M, et al. The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. Journal of Clinical Epidemiology. 2021.

Hwang G, et al. Assessing the potential of chatgpt for psychodynamic formulations in psychiatry: An exploratory study. Psychiatry Research. 2024;331:115655. DOI: https://doi.org/10.1016/j.psychres.2023.115655

Furukawa TA, et al. Harnessing AI to optimize thought records and facilitate cognitive restructuring in smartphone CBT: An exploratory study. Cognitive Therapy and Research. 2023;47(6):887–893. DOI: https://doi.org/10.1007/s10608-023-10411-7

Bucur A-M. Utilizing chatgpt generated data to retrieve depression symptoms from social media. 2023. DOI: https://doi.org/10.1007/978-3-031-71736-9_14

Hashem R, et al. AI to the rescue: Exploring the potential of chatgpt as a teacher ally for workload relief and burnout prevention. Research and Practice in Technology Enhanced Learning. 2024;19:023. DOI: https://doi.org/10.58459/rptel.2024.19023

Gabor-Siatkowska K, et al. AI to train AI: Using chatgpt to improve the accuracy of a therapeutic dialogue system. Electronics. 2023;12(22). DOI: https://doi.org/10.3390/electronics12224694

Levkovich I, Elyoseph Z. Identifying depression and its determinants upon initiating treatment: Chatgpt versus primary care physicians. Family Medicine and Community Health. 2023;11(4). DOI: https://doi.org/10.1136/fmch-2023-002391

Montag C, et al. On artificial intelligence and global mental health. Asian Journal of Psychiatry. 2023;103855. DOI: https://doi.org/10.1016/j.ajp.2023.103855

Dougherty RF, et al. Psilocybin therapy for treatment resistant depression: prediction of clinical outcome by natural language processing. Psychopharmacology. 2023. DOI: https://doi.org/10.1007/s00213-023-06432-5

Bird JJ, Lotfi A. Generative transformer chatbots for mental health support: A study on depression and anxiety. In: Proceedings of the 16th International Conference on PErvasive Technologies Related to Assistive Environments, PETRA ’23; 2023 p. 475–479. New York, NY, USA: Association for Computing Machinery. DOI: https://doi.org/10.1145/3594806.3596520

Brooks JA, et al. Emotion expression estimates to measure and improve multimodal social-affective interactions. In: Companion Publication of the 25th International Conference on Multimodal Interaction, ICMI ’23 Companion; 2023 p. 353–358. New York, NY, USA: Association for Computing Machinery. DOI: https://doi.org/10.1145/3610661.3616129

Bokolo Biodoumoye George, Liu Qingzhong. Deep Learning-Based Depression Detection from Social Media: Comparative Evaluation of ML and Transformer Techniques. Electronics. 2023;12(21):4396. Disponível em: https://www.mdpi.com/2079-9292/12/21/4396. DOI: 10.3390/electronics12214396. DOI: https://doi.org/10.3390/electronics12214396

Zhou W, et al. Identifying rare circumstances preceding female firearm suicides: Validating a large language model approach. JMIR Ment Health. 2023;10. DOI: https://doi.org/10.2196/49359

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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