| Resumen |
In this study titled, the crucial relevance of early detection of issues in the context of Agile Sprints is highlighted. It explores how proactive issue detection, supported by machine learning, can be a key support piece for effective risk analysis in agile project management. Furthermore, the importance of anticipating challenges in Agile Sprints and maintaining product quality with the help of predictive capabilities provided by machine learning is emphasized. Additionally, it is suggested that in future research, a more in-depth exploration be conducted into how other methodologies could complement or further enhance the application of machine learning techniques in this context. Finally, a comprehensive view is provided, projecting the possibility of improving project success through the strategic combination of proactive issue detection and machine learning capabilities in Agile Sprints. © 2024 by the International Institute of Informatics and Systemics. All rights reserved. |
