Competitive advantage in healthcare based on augmentation of clinical images with artificial intelligence: case study of the 'Sambias' project

Alessandra D'Amico, Michele Di Capua, Emanuel Di Nardo, Joanna Rosak-Szyrocka, Giuseppe Tortorella and Giuseppe Festa

International Journal of Managerial and Financial Accounting, 2024, vol. 16, issue 1, 1-16

Abstract: In the era of artificial intelligence, and particularly machine learning and deep learning models, the availability of large datasets is crucial to develop innovative and effective services, especially in the healthcare field. In this context, one essential requirement is access to verified information for contextualising/enriching the data. The SAMBIAS project analysed in this study involves the implementation of a software platform for data sharing in clinical scenarios, with the main objective of providing specific medical datasets to improve the competitiveness of the healthcare organisation from a general point of view. The platform, which is accessible via the web, provides on-demand, augmented sets of clinical situations, based on the enormous amounts of data that are collected by the health information systems of healthcare organisations. The case under investigation here is the Casa di Cura Tortorella s.p.a., Salerno, Italy. The implications of this platform are discussed in terms of more efficient performance.

Keywords: healthcare; artificial intelligence; machine learning; deep learning; data augmentation; business process management; business process improvement. (search for similar items in EconPapers)
Date: 2024
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