Abstract: At present, the development of chatbots is one of the key activities for the diagnosis of Covid-19. The aim is to understand how these chatbots operate in the health area to make a respective diagnosis. The purpose of the research is to determine the state of the art on the use of chatbots and its impact on Covid-19 diagnosis during the last 2 years. The data sources that have been consulted are IEEE Xplore, Taylor & Francis Online, ProQuest, World Wide Science, Science Direct, Microsoft Academic, Google Scholar, ACM Digital Library, Wiley Online Library, and ETHzurich. The search strategy identified 5701 papers, of which 101 papers were selected through 8 selection criteria and 7 quality assessments. This review presents discussions regarding the methodologies used for chatbot development, i.e., what are the purposes and impact of using chatbots for Covid-19 diagnosis. In addition, this is presents the results of how important the development and implementation of chatbots are in the area of health in the face of this pandemic.

Antony Albites-Tapia, Javier Gamboa-Cruzado, Junior Almeyda-Ortiz and Alberto Moreno Lázaro, “Chatbots for the Detection of Covid-19: A Systematic Review of the Literature” International Journal of Advanced Computer Science and Applications(IJACSA), 13(4), 2022. http://dx.doi.org/10.14569/IJACSA.2022.01304113

@article{Albites-Tapia2022,
title = {Chatbots for the Detection of Covid-19: A Systematic Review of the Literature},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.01304113},
url = {http://dx.doi.org/10.14569/IJACSA.2022.01304113},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {4},
author = {Antony Albites-Tapia and Javier Gamboa-Cruzado and Junior Almeyda-Ortiz and Alberto Moreno Lázaro}
}