Use of Image-Based Machine Learning and Quantum Learning for Subsurface Characterization

The proposed thesis aims to explore novel applications of machine learning for subsurface characterization. In the first chapter, an image-based data-driven workflow is proposed to characterize oil viscosity from side-wall rock sample images. Informative features are extracted from the rock sample images deploying several image-based filters and statistical models. Both regression and classification tasks are performed on the preprocessed data. The proposed workflow shows promising results for viscosity classification whereas future work is needed to improve the regression performance. The second and third chapters explore the application of quantum-enhanced machine learning models for lithology classification and the resulting comparison with classical machine learning models. The second chapter compares a quantum support vector machine with a traditional support vector classifier for lithology classification from well log data. Different sample sizes are tested to understand if a quantum advantage is obtained when the available data is limited. The third chapter investigates the application of both quantum support vector and variational quantum classifier for binary lithology classification. The score distribution obtained from testing the models with multiple iterations gives more insight on the current performance capabilities of quantum-enhanced machine models when compared to artificial networks. Overall, although a quantum advantage is not observed in both chapters, this work opens the door to future applications of quantum-enhanced machine learning for subsurface characterization

Effectiveness of cardiac resynchronization therapy in heart failure patients with valvular heart disease: comparison with patients affected by ischaemic heart disease or dilated cardiomyopathy. The InSync/InSync ICD Italian Registry

AimsTo analyse the effectiveness of cardiac resynchronization therapy (CRT) in patients with valvular heart disease (a subset not specifically investigated in randomized controlled trials) in comparison with ischaemic heart disease or dilated cardiomyopathy patients.Methods and resultsPatients enrolled in a national registry were evaluated during a median follow-up of 16 months after CRT implant. Patients with valvular heart disease treated with CRT (n = 108) in comparison with ischaemic heart disease (n = 737) and dilated cardiomyopathy (n = 635) patients presented: (i) a higher prevalence of chronic atrial fibrillation, with atrioventricular node ablation performed in around half of the cases; (ii) a similar clinical and echocardiographic profile at baseline; (iii) a similar improvement of LVEF and a similar reduction in ventricular volumes at 6-12 months; (iv) a favourable clinical response at 12 months with an improvement of the clinical composite score similar to that occurring in patients with dilated cardiomyopathy and more pronounced than that observed in patients with ischaemic heart disease; (v) a long-term outcome, in term of freedom from death or heart transplantation, similar to patients affected by ischaemic heart disease and basically more severe than that of patients affected by dilated cardiomyopathy.ConclusionIn 'real world' clinical practice, CRT appears to be effective also in patients with valvular heart disease. However, in this group of patients the outcome after CRT does not precisely overlap any of the two other groups of patients, for which much more data are currently available

Personalizing Cancer Pain Therapy: Insights from the Rational Use of Analgesics (RUA) Group

Introduction: A previous Delphi survey from the Rational Use of Analgesics (RUA) project involving Italian palliative care specialists revealed some discrepancies between current guidelines and clinical practice with a lack of consensus on items regarding the use of strong opioids in treating cancer pain. Those results represented the basis for a new Delphi study addressing a better approach to pain treatment in patients with cancer. Methods: The study consisted of a two-round multidisciplinary Delphi study. Specialists rated their agreement with a set of 17 statements using a 5-point Likert scale (0 = totally disagree and 4 = totally agree). Consensus on a statement was achieved if the median consensus score (MCS) (expressed as value at which at least 50% of participants agreed) was at least 4 and the interquartile range (IQR) was 3–4. Results: This survey included input from 186 palliative care specialists representing all Italian territory. Consensus was reached on seven statements. More than 70% of participants agreed with the use of low dose of strong opioids in moderate pain treatment and valued transdermal route as an effective option when the oral route is not available. There was strong consensus on the importance of knowing opioid pharmacokinetics for therapy personalization and on identifying immediate-release opioids as key for tailoring therapy to patients’ needs. Limited agreement was reached on items regarding breakthrough pain and the management of opioid-induced bowel dysfunction. Conclusion: These findings may assist clinicians in applying clinical evidence to routine care settings and call for a reappraisal of current pain treatment recommendations with the final aim of optimizing the clinical use of strong opioids in patients with cancer