Abstract
In this paper, we will explore the potential of knowledge discovery from bio-medical databases in health safeguard, by illustrating two specific case studies, where different knowledge extraction techniques have been exploited. Specifically, we will first report on how machine learning and data mining algorithms can address the problem of food adulteration. Then, we will show how process mining techniques can be adopted to analyze the quality of patient care provided at a specific health care organization. Working in the bio-medical application domain has not only led to consistent and concretely useful experimental outcomes, but has also required some significant methodological advances with respect to the existing literature.
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Notes
- 1.
This does not mean that techniques like PCA are not used in machine learning approaches, however they are often adopted as preliminary step (e.g. for feature reduction) rather than as main techniques to identify classes as in SIMCA analysis [32].
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Leonardi, G., Montani, S., Portinale, L., Quaglini, S., Striani, M. (2019). Discovering Knowledge Embedded in Bio-medical Databases: Experiences in Food Characterization and in Medical Process Mining. In: Esposito, A., Esposito, A., Jain, L. (eds) Innovations in Big Data Mining and Embedded Knowledge. Intelligent Systems Reference Library, vol 159. Springer, Cham. https://doi.org/10.1007/978-3-030-15939-9_7
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