4 Contributo in Atti di Convegno (Proceeding)

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Aldo Castellani (1874-1971), il medico fascista che lavorò per la resistenza

79 Aldo Castellani (1874 - 1971), il medico fascista che lAldo Castellani è sicuramente una delle figure più rilevanti della medicina mondiale del Ventesimo secolo. Il suo internazionalismo esistenziale e il suo fecondo attivismo nella ricerca biomedica non possono però far dimenticare la pagina complicata e cont roversa dei suoi rapporti con il regime fascista. Castellani fu a lungo medico ascoltato e apprezzato da Mussolini e da molti alti gerarchi del regime che ne utilizzarono spess...

RobustRecSys @ RecSys2024: Design, Evaluation and Deployment of Robust Recommender Systems

In recent years, recommender systems have become indispensable tools in various domains, aiding users in discovering relevant content amidst the overwhelming amount of available material. However, the effectiveness and reliability of these systems are often hindered by various challenges such as data perturbations, missing data, noise, and bias. In this workshop, we aim to explore and address these challenges by focusing on the development of robust recommender systems. Robustness in recommen...

Virtual Scanner: Leveraging Resilient Generative AI for Radiological Imaging in the Era of Medical Digital Twins

Advancements in generative artificial intelligence (AI) are setting the stage for transformative changes in medical imaging, particularly through the development of the Virtual Scanner. This innovative approach leverages resilient generative AI to synthesize radiological images, addressing critical challenges in the field such as data scarcity, patient exposure to radiation, and the limitations of current imaging technologies. By harnessing the power of Generative Adversarial Networks (GANs) ...

Multi-Dataset Multi-Task Learning for COVID-19 Prognosis

In the fight against the COVID-19 pandemic, leveraging artificial intelligence to predict disease outcomes from chest radiographic images represents a significant scientific aim. The challenge, however, lies in the scarcity of large, labeled datasets with compatible tasks for training deep learning models without leading to overfitting. Addressing this issue, we introduce a novel multi-dataset multi-task training framework that predicts COVID-19 prognostic outcomes from chest X-rays (CXR) by ...

Prediction of DC/DC Boost Converter Switching Power Losses Using a Backpropagation Algorithm Neural Network

One significant aspect that influences the overall efficiency of the DC/DC boost converters is the switching power losses incurred during operation. Predicting and optimizing these losses is essential for enhancing converter efficiency and reducing energy wastage. This article explores the utilization of a backpropagation algorithm neural network approach for predicting switching power losses in DC/DC boost converters. By combining the optimization capabilities of backpropagation algorithms w...

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