Twitter users perceptions of AI-based e-learning technologies.

Today, teaching and learning paths increasingly intersect with technologies powered by emerging artificial intelligence (AI).This work analyses public opinions and sentiments about AI applications that affect e-learning, such as ChatGPT, virtual and augmented reality, microlearning, mobile learning, adaptive learning, and gamification. The way people perceive technologies fuelled by artificial intelligence can be tracked in real time in microblog messages promptly shared by Twitter users, who currently constitute a large and ever-increasing number of individuals.

Covid-19 vaccines in Italian public opinion: Identifying key issues using Twitter and Natural Language Processing.

The COVID-19 pandemic has changed society and people's lives. The vaccination campaign started December 27th 2020 in Italy, together with most countries in the European Union. Social media platforms can offer relevant information about how citizens have experienced and perceived the availability of vaccines and the start of the vaccination campaign.

Tweet topics and sentiments relating to distance learning among Italian Twitter users.

The outbreak of COVID-19 forced a dramatic shift in education, from in-person learning to an increased use of distance learning over the past 2 years. Opinions and sentiments regarding this switch from traditional to remote classes can be tracked in real time in microblog messages promptly shared by Twitter users, who constitute a large and ever-increasing number of individuals today. Given this framework, the present study aims to investigate sentiments and topics related to distance learning in Italy from March 2020 to November 2021.

The combined role of biomarkers and interim PET scan in prediction of treatment outcome in classical Hodgkin's lymphoma: a retrospective, European, multicentre cohort study.

Background: Early-interim fluorodeoxyglucose (FDG)-PET scan after two ABVD (doxorubicin, bleomycin, vinblastine, and dacarbazine) chemotherapy courses (PET-2) represents the most effective predictor of treatment outcome in classical Hodgkin's lymphoma. We aimed to assess the predictive value of PET-2 combined with tissue biomarkers in neoplastic and microenvironmental cells for this disease.

Methods: We enrolled 208 patients with classical Hodgkin's lymphoma and treated with ABVD (training set), from Jan 1, 2002, to Dec 31, 2009, and validated the results in a fully matched independent cohort of 102 patients with classical Hodgkin's lymphoma (validation set), enrolled from Jan 1, 2008, to Dec 31, 2012.