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Data Quality as a Key Factor in the Application of Artificial Intelligence Techniques in Clinical Nursing
Noelia Palomares Bonet1, Carlos Cano Genovés2, Reyes Grangel Seguer1
1Grupo de Investigación en Aprendizaje Automático para Entornos Inteligentes. Departamento de Lenguajes y Sistemas Informáticos. Universitat Jaume I.
Abstract:
The integration of Artificial Intelligence (AI) across all professional and social spheres, and especially in the healthcare context, is transforming the way processes are carried out. In the field of clinical nursing, the use of AI-based techniques can significantly help optimize care processes, where machine learning and process mining can improve patient care. However, its application in this context depends on a key factor: the availability of high-quality data, the absence of which limits the development of reliable models. Building on standards related to data governance and data quality, this article examines the dimensions that define data quality within the healthcare domain. The aim is to identify which dimensions are necessary for the application of AI techniques in this context and subsequently analyse whether the different standards proposed in the literature meet the identified dimensions. Finally, the paper outlines the main healthcare standards designed to ensure data quality, analysing how they help address these issues. In conclusion, it highlights the potential of these standards to contribute to improving data quality and enable the effective use of AI to enhance nursing processes.
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