Chatbots en la identificación de problemas de lactancia materna: evaluación del desempeño

Autores/as

  • Ari Pereira de Araújo Neto Universidade Federal do Delta do Parnaíba
  • Giovanny Rebouças Pinto Universidade Federal do Delta do Parnaíba
  • Joeckson dos Santos Corrêa Universidade Federal do Maranhão
  • Liane Batista da Cruz Soares Universidade Federal do Maranhão
  • Christyann Lima Campos Batista Universidade Federal do Maranhão
  • Feliciana Santos Pinheiro Universidade Federal do Maranhão
  • Ariel Soares Teles Instituto Federal do Maranhão

DOI:

https://doi.org/10.59681/2175-4411.v16.iEspecial.2024.1370

Palabras clave:

Lactancia, Inteligencia Artificial, Sistemas Especialistas

Resumen

Objetivo: Este estudio tuvo como objetivo evaluar el desempeño de chatbots de inteligencia artificial en la identificación de problemas relacionados con la lactancia. Metodo: El estudio evaluó OpenAI ChatGPT-3.5, Microsoft Copilot, Google Gemini y Lhia en la identificación de problemas de la lactancia. El chatbot Lhia está siendo desarrollado por nuestro equipo de investigadores. A través del consenso entre profesionales de salud especialistas en lactancia, se creó un conjunto de datos de informes de quejas clínicas principales anotadas en los registros médicos del Hospital Universitario de la Universidad Federal de Maranhão para las pruebas con tres enfoques de comandos del tipo zero-shot. Resultados: El mejor desempeño fue con ChatGPT-3.5, que presentó una precisión que varió del 79% al 93%, fallback del 0% al 7% y F1-score del 75% al 100%. Conclusión: Los chatbots de inteligencia artificial pueden ser una herramienta prometedora para asistir a madres y profesionales de salud en la detección temprana de problemas en la lactancia.

Biografía del autor/a

Ari Pereira de Araújo Neto, Universidade Federal do Delta do Parnaíba

Mestre em Biotecnologia, Programa de Pós-Graduação em Biotecnologia, Universidade Federal do Delta do Parnaíba, Parnaíba (PI), Brasil.

Giovanny Rebouças Pinto, Universidade Federal do Delta do Parnaíba

Doutor em Ciências Biológicas, Programa de Pós-Graduação em Biotecnologia, Universidade Federal do Delta do Parnaíba, Parnaíba (PI), Brasil.

Joeckson dos Santos Corrêa, Universidade Federal do Maranhão

Mestre em Ciência da Computação, Programa de Pós-Graduação em Ciência da Computação, Universidade Federal do Maranhão, São Luís (MA), Brasil.

Liane Batista da Cruz Soares, Universidade Federal do Maranhão

Mestra em Gestão de Programas e Serviços de Saúde, Banco de Leite Humano, Hospital Universitário da Universidade Federal do Maranhão, São Luís (MA), Brasil.

Christyann Lima Campos Batista, Universidade Federal do Maranhão

Doutor em Pediatria, Banco de Leite Humano, Hospital Universitário da Universidade Federal do Maranhão, São Luís (MA), Brasil.

Feliciana Santos Pinheiro, Universidade Federal do Maranhão

Doutora em Pediatria, Departamento de Medicina III, Universidade Federal do Maranhão, São Luís (MA), Brasil.

Ariel Soares Teles, Instituto Federal do Maranhão

Doutor em Engenharia Elétrica, Instituto Federal do Maranhão, Araioses (MA), Brasil.

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Publicado

2024-11-19

Cómo citar

de Araújo Neto, A. P., Pinto, G. R., Corrêa, J. dos S., Soares, L. B. da C., Batista, C. L. C., Pinheiro, F. S., & Teles, A. S. (2024). Chatbots en la identificación de problemas de lactancia materna: evaluación del desempeño. Journal of Health Informatics, 16(Especial). https://doi.org/10.59681/2175-4411.v16.iEspecial.2024.1370

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