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.

Discovering knowledge embedded in bio-medical databases: Experiences in food characterization and in medical process mining

Leonardi G.;Montani S.;Portinale L.;Quaglini S.;
2019-01-01

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.
2019
978-3-030-15938-2
978-3-030-15939-9
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11571/1449164
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