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AI-HOPE Lung cancer: building a predictive tool for metastatic lung cancer

Metastatic non-small-cell lung cancer (NSCLC) represents a heterogeneous disease with markedly variable outcomes, and reliable prognostic and predictive tools are urgently needed, particularly in the real-world setting. The AI-HOPE study was designed as an ambispective, multicentre project to collect real-world data and develop machine-learning models capable of predicting clinical endpoints in patients with metastatic NSCLC receiving first-line immunotherapy with or without chemotherapy. In ...

Leveraging real-world data with machine learning to disentangle the complexity of multimorbid internal medicine patients

The application of machine learning to healthcare real-world data is emerging as a complementary approach to clinical trials for enabling data-driven decision-making in the evolving population of complex patients managed in the internal medicine setting. To fully realise this potential, significant challenges remain, including data availability and quality limitations and the absence of standardized protocols for model development. In this thesis, we explore how to build an end-to-end machine...

Kant on Analogy: The Problem of Predicating the Noumenon in the Precritical Works

The dissertation aims to analyze Kant’s use of the concept of analogy in his precritical writings, while also reconstructing the historical development of the notion of analogy in order to provide a more accurate historical contextualization of Kant’s works. In doing so, it seeks to demonstrate that the characteristically critical concepts of regulative and constitutive knowledge can be traced back to the precritical period, specifically to Kant’s use of analogy as a means of addressing the p...

CLIMATE CHANGE AND MOTIVATION: VALUES, KNOWLEDGE, EDUCATION

sostenibilità, etica ambientale, filosofia morale, responsabilità individuale e collettiva, cambiamento climatico, educazione ambientale, educazione alla sostenibilità, comunicazione ambientale

Artificial intelligence of imaging and clinical neurological data for predictive, preventive and personalized medicine for Gliomas

Diffuse gliomas represent the most common malignant primary brain tumors in adults and are now classified according to integrated histopathological and molecular criteria as proposed by the latest WHO CNS5 guidelines. Among the defining molecular alterations, mutations in isocitrate dehydrogenase (IDH) genes have emerged as pivotal for prognosis and therapeutic stratification with substantial implications for clinical outcome. However, current determination of IDH status relies primarily on i...

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