3 resultados para Multiple Additive Regression Trees (MART)

em AMS Tesi di Dottorato - Alm@DL - Università di Bologna


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Questa tesi descrive alcuni studi di messa a punto di metodi di analisi fisici accoppiati con tecniche statistiche multivariate per valutare la qualità e l’autenticità di oli vegetali e prodotti caseari. L’applicazione di strumenti fisici permette di abbattere i costi ed i tempi necessari per le analisi classiche ed allo stesso tempo può fornire un insieme diverso di informazioni che possono riguardare tanto la qualità come l’autenticità di prodotti. Per il buon funzionamento di tali metodi è necessaria la costruzione di modelli statistici robusti che utilizzino set di dati correttamente raccolti e rappresentativi del campo di applicazione. In questo lavoro di tesi sono stati analizzati oli vegetali e alcune tipologie di formaggi (in particolare pecorini per due lavori di ricerca e Parmigiano-Reggiano per un altro). Sono stati utilizzati diversi strumenti di analisi (metodi fisici), in particolare la spettroscopia, l’analisi termica differenziale, il naso elettronico, oltre a metodiche separative tradizionali. I dati ottenuti dalle analisi sono stati trattati mediante diverse tecniche statistiche, soprattutto: minimi quadrati parziali; regressione lineare multipla ed analisi discriminante lineare.

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Background: Clinical trials have demonstrated that selected secondary prevention medications for patients after acute myocardial infarction (AMI) reduce mortality. Yet, these medications are generally underprescribed in daily practice, and older people are often absent from drug trials. Objectives: To examine the relationship between adherence to evidence-based (EB) drugs and post-AMI mortality, focusing on the effects of single therapy and polytherapy in very old patients (≥80 years) compared with elderly and adults (<80 years). Methods: Patients hospitalised for AMI between 01/01/2008 and 30/06/2011 and resident in the Local Health Authority of Bologna were followed up until 31/12/2011. Medication adherence was calculated as the proportion of days covered for filled prescriptions of angiotensin-converting enzyme inhibitors (ACEIs)/angiotensin receptor blockers (ARBs), β-blockers, antiplatelet drugs, and statins. We adopted a risk set sampling method, and the adjusted relationship between medication adherence (PDC≥75%) and mortality was investigated using conditional multiple logistic regression. Results: The study population comprised 4861 patients. During a median follow-up of 2.8 years, 1116 deaths (23.0%) were observed. Adherence to the 4 EB drugs was 7.1%, while nonadherence to any of the drugs was 19.7%. For both patients aged ≥80 years and those aged <80 years, rate ratios of death linearly decreased as the number of EB drugs taken increased. There was a significant inverse relationship between adherence to each of 4 medications and mortality, although its magnitude was higher for ACEIs/ARBs (adj. rate ratio=0.60, 95%CI=0.52–0.69) and statins (0.60, 0.50–0.72), and lower for β-blockers (0.75, 0.61–0.92) and antiplatelet drugs (0.73, 0.63–0.84). Conclusions: The beneficial effect of EB polytherapy on long-term mortality following AMI is evident also in nontrial older populations. Given that adherence to combination therapies is largely suboptimal, the implementation of strategies and initiatives to increase the use of post-AMI secondary preventive medications in old patients is crucial.

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The instability of river bank can result in considerable human and land losses. The Po river is the most important in Italy, characterized by main banks of significant and constantly increasing height. This study presents multilayer perceptron of artificial neural network (ANN) to construct prediction models for the stability analysis of river banks along the Po River, under various river and groundwater boundary conditions. For this aim, a number of networks of threshold logic unit are tested using different combinations of the input parameters. Factor of safety (FS), as an index of slope stability, is formulated in terms of several influencing geometrical and geotechnical parameters. In order to obtain a comprehensive geotechnical database, several cone penetration tests from the study site have been interpreted. The proposed models are developed upon stability analyses using finite element code over different representative sections of river embankments. For the validity verification, the ANN models are employed to predict the FS values of a part of the database beyond the calibration data domain. The results indicate that the proposed ANN models are effective tools for evaluating the slope stability. The ANN models notably outperform the derived multiple linear regression models.