Mobile application of Medical diagnosis with the Implementation of Artificial Intelligence in Metropolitan Lima
How to Cite?
Carlos Caceres-Gonzales, Jose Delgado-Gomez, Alexi Delgado, Enrique Lee Huamaní, "Mobile application of Medical diagnosis with the Implementation of Artificial Intelligence in Metropolitan Lima," International Journal of Engineering Trends and Technology, vol. 69, no. 6, pp. 199-205, 2021. Crossref, https://doi.org/10.14445/22315381/IJETT-V69I6P229
The objective is to avoid a greater number of infections, diagnosing patients through a mobile application that will solve and avoid the crowds of people outside the medical centers, The operation used was XP since we have the established weeks and processes to follow stages, which There are 4, planning, design, coding and testing, balsamiq was used for the prototypes, with the help of AI and “Android” mobile application; The statistical data obtained comes from the Peruvian medical college, which provides us with exact data on how the situation is in our society and we can apply it to solve the problem.
Artificial intelligence, Component: mobile app, Medical diagnosis.
 Quispe-Juli, C., Vela-Anton, P., Meza-Rodriguez, M., & Moquillaza-Alcántara, V. (2020). COVID-19: A Pandemic in the Age of Digital Health. Biomedical Informatics Unit in Global Health, 1–19.
 Martínez-García, D. N., Dalgo-Flores, V. M., Herrera-López, J. L., Analuisa-Jiménez, E. I., & Velasco-Acurio, E. F. (2019). Advances in artificial intelligence in health. Domain of Sciences, 5 (3), 603.
 Montenegro-López, D. (2020). Use of technologies in the place of care for the management of the COVID-19 pandemic in Colombia. Pan American Journal of Public Health, 44, 1.
 Arias, V., Salazar, J., Contreras, J., & Chacón, G. (2019). An introduction to the applications of artificial intelligence in Medicine: Historical aspects. Latin American Journal of Hypertension, 14 (5), 11.
 Lei, H., Ganjeizadeh, F., Jayachandran, P. K., & Ozca, P. (2017). A statistical analysis of the effects of Scrum and Kanban on software development projects. Robotics and Computer-Integrated Manufacturing, 43, 59–67.
 Baraças Figueiredo Correio, L., & Leme Fleury, A. (2019). Design Sprint versus Design Thinking: A comparative analysis. Gestão Da Produção Operações e Sistemas Magazine, 14 (5), 23–47.
 Fallis, A. G. (2013). Current Methodology XP Methodology. Journal of Chemical Information and Modeling, 53 (9), 1689-1699.
 M. R. Arangüena Yllanes, SWGPI WEB SYSTEM IN THE MANAGEMENT OF RESEARCH PROJECTS EVALUATED WITH ISO / IEC 9126. Revista de Investigaciones. 7, 537–547 (2018).
 XP / Architecture: An Agile Model for Scaling XP. Colombian computer magazine. 13, 124-140 (2012).
 V. Lope Salvador, X. Mamaqi, J. Vidal Bordes, Artificial intelligence. ICONO14 Magazine Scientific journal of Communication and Emerging Technologies. 18, 58–88 (2020).
 Baltrusaitis, T., Ahuja, C., & Morency, LP (2019, February 1). Multimodal Machine Learning: A Survey and Taxonomy. IEEE Transactions on Machine Intelligence and Pattern Analysis. IEEE Informatics Society.
 B. Montero Molina, H. Cevallos Vite, J. Dávila Cuesta, Agile methodologies versus traditional ones in the software development process. Spirals multidisciplinary research journal ISSN: 2550-6862. 2 (2018) 114-121.