Nicola Lazzarini

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Nicotine dependence is characteristically a chronic and relapsing disease. Although 75%-85% of smokers would like to quit, and one-third make at least three serious lifetime attempts, less than 50% of smokers succeed in stopping before the age of 60. Relevant and complex factors contributing to sustained cigarette consumption, and strongly implicated in the(More)
Many classification problems must deal with imbalanced datasets where one class – the majority class – outnumbers the other classes. Standard classification methods do not provide accurate predictions in this setting since classification is generally biased towards the majority class. The minority classes are oftentimes the ones of interest (e.g., when they(More)
Functional networks play an important role in the analysis of biological processes and systems. The inference of these networks from high-throughput (-omics) data is an area of intense research. So far, the similarity-based inference paradigm (e.g. gene co-expression) has been the most popular approach. It assumes a functional relationship between genes(More)
Correspondence: Fiammetta Cosci Department of Psychology, University of Florence, via di San Salvi 12, 50135 Florence, italy Tel + 39 055 623 7811 Fax +39 055 623 6047 email fiammetta.cosci@unifi.it Abstract: Nicotine dependence is characteristically a chronic and relapsing disease. Although 75%–85% of smokers would like to quit, and one-third make at least(More)
Current -omics technologies are able to sense the state of a biological sample in a very wide variety of ways. Given the high dimensionality that typically characterises these data, relevant knowledge is often hidden and hard to identify. Machine learning methods, and particularly feature selection algorithms, have proven very effective over the years at(More)
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