Evaluation of a Chatbot Powered by ChatGPT for the Preliminary Diagnosis of Dengue

Authors

  • Raúl Jáuregui-Velarde Universidad Privada Norbert Wiener
  • Domingo Hernández Celis Universidad Nacional Federico Villarreal https://orcid.org/0000-0002-9759-4436
  • Pedro Molina-Velarde Universidad Tecnológica del Perú
  • Cesar Yactayo-Arias
  • Laberiano Andrade-Arenas "Universidad de Ciencias y Humanidades"

DOI:

https://doi.org/10.3991/ijoe.v20i01.45029

Keywords:

artificial intelligence, chatbot, chatGPT, dengue, dengue diagnosis

Abstract


Dengue poses a public-health challenge in several regions. Early detection is essential to reduce the impact of a condition, and artificial intelligence (AI) and chatbots provide new opportunities to enhance diagnosis. This study evaluates the effectiveness of integrating a chatbot with ChatGPT version GPT-3.5 for the preliminary diagnosis of dengue and its contribution to timely detection. To evaluate this, two types of tests were conducted using a dataset of 30 dengue cases. In the first test, the chatbot was evaluated without being trained with dengue symptoms. In the second test, however, the model was trained using dengue symptoms obtained from official websites such as the World Health Organization (WHO) and the Pan American Health Organization (PAHO). The performance of the chatbot was evaluated using the confusion matrix, performance metrics, and user satisfaction. The results of the second test showed impressive performance, with accuracy, sensitivity, and specificity of 100%. This surpassed the first test, which achieved accuracy, sensitivity, and specificity of 83%, 80%, and 90%, respectively. In addition, 15 users reported positive satisfaction, with an overall average rating of 4.25 out of 5. In conclusion, these results highlight the effectiveness of the chatbot as a valuable public health tool for the early detection and management of dengue. It is important to note that, despite the remarkable diagnostic results of the chatbot integrated with ChatGPT, it does not replace medical judgment.

Cover iJOE – Vol 20, No 01, 2024

Downloads

Published

2024-01-12

How to Cite

Jáuregui-Velarde, R., Hernández Celis, D., Molina-Velarde, P. ., Yactayo-Arias, C. ., & Andrade-Arenas, L. (2024). Evaluation of a Chatbot Powered by ChatGPT for the Preliminary Diagnosis of Dengue. International Journal of Online and Biomedical Engineering (iJOE), 20(01), pp. 58–73. https://doi.org/10.3991/ijoe.v20i01.45029

Issue

Vol. 20 No. 01 (2024)

Section

Papers

License

Copyright (c) 2023 Laberiano Andrade Arenas, Domingo Hernández Celis, Pedro Molina-Velarde, Cesar Yactayo-Arias

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

The submitting author warrants that the submission is original and that she/he is the author of the submission together with the named co-authors; to the extend the submission incorporates text passages, figures, data or other material from the work of others, the submitting author has obtained any necessary permission.
Articles in this journal are published under the Creative Commons Attribution Licence (CC-BY What does this mean?). This is to get more legal certainty about what readers can do with published articles, and thus a wider dissemination and archiving, which in turn makes publishing with this journal more valuable for you, the authors.
By submitting an article the author grants to this journal the non-exclusive right to publish it. The author retains the copyright and the publishing rights for his article without any restrictions.