Completed projects

General

• Development of a methodological review on statistical inference and distributed learning in health

Master’s

• Development of artificial intelligence techniques for the automated identification of electrical energy assets (2020-2022)
• Machine learning strategies for the diagnostic and the prediction of late adverse effects related to childhood lymphoblastic leukaemia treatment (2020-2022)
• Multi-task learning for image classification of renal tumors (2020-2023)
• Radiomics for the management of small renal masses (2022-2024)
• Resilient predictive models based on quantitative imaging to guide prostate cancer treatment (2021-2024)
• Exploration of radiomic characteristics complexity (2021-2024)

Bachelor’s

• Random forests in a distributed learning context (2022)

Internship

• Graph neural networks for predicting patient mortality within one year of hospital admission (2022)