Chatbot Implementation to Collect Data on Possible COVID-19 Cases and Release the Pressure on the Primary Health Care System
Wilmer Stalin Erazo, German Patricio Guerrero, Carlos Carrión Betancourt, Iván Sánchez
- Year
- 2020
- Citations
- 23
Abstract
Nowadays, the evolution of artificial intelligence is present in almost every field of the modern science and technology, because it is a powerful tool for analysis and quick decision making, enabling capacity to automate various processes in companies, government institutions, or research groups through one of the preferred techniques for automated software processes. Thus, the use of this kind tool has allowed us to develop a Chatbot (robot) that has the ability to simulate the conversation with a human being, to answer very specific questions [1]. Artificial intelligence has the ability to acquire, and achieve goals in the computer world, trying to emulate the way human intelligence process information. Currently, there are several creations in Chatbot that allows automating recurring processes, can decrease the response times of an activity, guarantee the availability of the service, and or omit the presence of a person, and it is very useful for process where there is a certain type of prevented behavior. In the health area, it is essential to have an assistant who knows how to give information at any time of the day, specially in a worldwide pandemic crises, but in funny hours is more complicated to have an online attendant to answer specific questions about the illness. The present work shows the results of an implementation of a Chatbot based on Artificial Intelligence to help the Medical Department at UDLA University in Ecuador, to detect possible cases of COVID-19, and for help to alleviate the saturated health system, and more importantly to collect information to prevent the dissemination of the infectious disease, we have created a platform to interact with possible infected persons who get the support from the University facilities.
Keywords
Related papers
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Fractional Differential Equations
Igor Podlubný
2025
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991