The completion of human DNA sequencing in the early 2000s initially generated widespread excitement and hope that it would revolutionize medicine. Over time, however, it revealed major limitations due to a lack of understanding of the highly complex genotype-phenotype pathway. Precision medicine...
01a Articolo in rivista
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Despite the great advances in HIV treatment, there are still several processes in the dynamics of the infection that are not yet fully understood. Some evidences show that when the therapy HAART is suspended, infection resumes, suggesting the existence of virus reservoirs; these have been...
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Existing consensus control algorithms for networked discrete-time linear systems have slow convergence to consensus trajectories due to limitations on the magnitude of the consensus gain. In this work we propose and analyze a new predictor-based consensus control protocol that recovers the positive...
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Recently, the new industrial paradigm of circular economy (CE) has acquired increasing attention. In a CE, the value of materials is preserved by keeping them for as long as possible in the economic system, overcoming the "traditional" linear model (take-waste-disposal). Despite its benefits in...
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Analysing visitors’ behaviour in a museum or in a cultural site is a crucial element to manage spaces and artworks arrangement as well as improving the visit experience. This paper presents the preliminary results of the ARTEMISIA project, exploiting Artificial Intelligence (AI) techniques to study...
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Federated Learning (FL) enables collaborative training of Machine Learning (ML) models across decentralized clients while preserving data privacy. One of the challenges that FL faces is when the clients’ data is not independent and identically distributed (non-IID). It is, therefore, crucial to...
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Federated Learning (FL) enables collaborative training of Machine Learning (ML) models across decentralized clients while preserving data privacy. One of the challenges that FL faces is when the clients’ data is not independent and identically distributed (non-IID). It is, therefore, crucial to...
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Data-driven health innovation may lead to develop targeted treatments using health data. We consider privacy-sensitive patients who may decide to share personal health data if compensated. Each patient does not internalize the impact of sharing data on drug innovation. We show that investment...
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Federated Learning (FL) enables collaborative training of Machine Learning (ML) models across decentralized clients while preserving data privacy. One of the challenges that FL faces is when the clients’ data is not independent and identically distributed (non-IID). It is, therefore, crucial to...
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Recently, the new industrial paradigm of circular economy (CE) has acquired increasing attention. In a CE, the value of materials is preserved by keeping them for as long as possible in the economic system, overcoming the "traditional" linear model (take-waste-disposal). Despite its benefits in...