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 ...

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 ...

In the field of lung cancer research, particularly in the analysis of overall survival (OS), artificial intelligence (AI) serves crucial roles with specific aims. Given the prevalent issue of missing data in the medical ...

• A DL-based decision support system predicting lung cancer prognosis.
• A transformer-based approach to cope with missing values without imputation.
• A model robust across different time granularities used to predict overall survival.

The COVID-19 pandemic has caused millions of cases and deaths and the AI-related scientific community, after being involved with detecting COVID-19 signs in medical images, has been now directing the efforts towards the development of ...

• Optimized multimodal end-to-end framework.
• Pareto multi-objective optimization ...

Since the beginning of the COVID-19 pandemic, more than 350 million cases and 5 million deaths have occurred. Since day one, multiple methods have been provided to diagnose patients who have been infected. Alongside the gold standard of laboratory ...

• On the use of chest X-ray to identify patients suffering from COVID-19.
• Pareto-...

The year 2020 was characterized by the COVID-19 pandemic that has caused, by the end of March 2021, more than 2.5 million deaths worldwide. Since the beginning, besides the laboratory test, used as the gold standard, many applications ...

The availability of the epidemiological data strongly affects the reliability of several mathematical models in tracing and forecasting COVID-19 pandemic, hampering a fair assessment of their relative performance. The marked difference between ...

• Mathematical modelling can provide valuable insights about COVID-19 dynamics proviso reliable epidemiological data.
• Poor quality of epidemiological data, especially due to the presence of asymptomatic people, affect the model accuracy.