TY - Generic T1 - GET-Viz: a library for automatic generation of visual dashboard for geographical time series T2 - 8th International Conference on Computational Social Science (IC2S2) Y1 - 2022 A1 - Fadda, Daniele A1 - Michela Natilli A1 - S Rinzivillo JF - 8th International Conference on Computational Social Science (IC2S2) CY - Chicago, USA ER - TY - JOUR T1 - The long-tail effect of the COVID-19 lockdown on Italians’ quality of life, sleep and physical activity JF - Scientific Data Y1 - 2022 A1 - Michela Natilli A1 - Alessio Rossi A1 - Trecroci, Athos A1 - Cavaggioni, Luca A1 - Merati, Giampiero A1 - Formenti, Damiano AB - From March 2020 to May 2021, several lockdown periods caused by the COVID-19 pandemic have limited people’s usual activities and mobility in Italy, as well as around the world. These unprecedented confinement measures dramatically modified citizens’ daily lifestyles and behaviours. However, with the advent of summer 2021 and thanks to the vaccination campaign that significantly prevents serious illness and death, and reduces the risk of contagion, all the Italian regions finally returned to regular behaviours and routines. Anyhow, it is unclear if there is a long-tail effect on people’s quality of life, sleep- and physical activity-related behaviours. Thanks to the dataset described in this paper, it will be possible to obtain accurate insights of the changes induced by the lockdown period in the Italians’ health that will permit to provide practical suggestions at local, regional, and state institutions and companies to improve infrastructures and services that could be beneficial to Italians’ well being. VL - 9 UR - https://www.nature.com/articles/s41597-022-01376-5 ER - TY - Generic T1 - Semantic Enrichment of XAI Explanations for Healthcare T2 - 24th International Conference on Artificial Intelligence Y1 - 2022 A1 - Corbucci, Luca A1 - Anna Monreale A1 - Cecilia Panigutti A1 - Michela Natilli A1 - Smiraglio, Simona A1 - Dino Pedreschi AB - Explaining black-box models decisions is crucial to increase doctors' trust in AI-based clinical decision support systems. However, current eXplainable Artificial Intelligence (XAI) techniques usually provide explanations that are not easily understandable by experts outside of AI. Furthermore, most of the them produce explanations that consider only the input features of the algorithm. However, broader information about the clinical context of a patient is usually available even if not processed by the AI-based clinical decision support system for its decision. Enriching the explanations with relevant clinical information concerning the health status of a patient would increase the ability of human experts to assess the reliability of the AI decision. Therefore, in this paper we present a methodology that aims to enable clinical reasoning by semantically enriching AI explanations. Starting from a medical AI explanation based only on the input features provided to the algorithm, our methodology leverages medical ontologies and NLP embedding techniques to link relevant information present in the patient's clinical notes to the original explanation. We validate our methodology with two experiments involving a human expert. Our results highlight promising performance in correctly identifying relevant information about the diseases of the patients, in particular about the associated morphology. This suggests that the presented methodology could be a first step toward developing a natural language explanation of AI decision support systems. JF - 24th International Conference on Artificial Intelligence ER - TY - Generic T1 - SoBigData++: European Integrated Infrastructure for Social Mining and Big Data Analytics. T2 - 30th Italian Symposium on Advanced Database Systems (SEBD – Sistemi Evoluti per Basi di Dati) Y1 - 2022 A1 - Trasarti, Roberto A1 - Grossi, Valerio A1 - Michela Natilli A1 - Rapisarda, Beatrice AB - SoBigData RI has the ambition to support the rising demand for cross-disciplinary research and innovation on the multiple aspects of social complexity from combined data and model-driven perspectives and the increasing importance of ethics and data scientists’ responsibility as pillars of trustworthy use of Big Data and analytical technology. Digital traces of human activities offer a considerable opportunity to scrutinize the ground truth of individual and collective behaviour at an unprecedented detail and on a global scale. This increasing wealth of data is a chance to understand social complexity, provided we can rely on social mining, i.e., adequate means for accessing big social data and models for extracting knowledge from them. SoBigData RI, with its tools and services, empowers researchers and innovators through a platform for the design and execution of large-scale social mining experiments, open to users with diverse backgrounds, accessible on the cloud (aligned with EOSC), and also exploiting supercomputing facilities. Pushing the FAIR (Findable, Accessible, Interoperable) and FACT (Fair, Accountable, Confidential, and Transparent) principles will render social mining experiments more efficiently designed, adjusted, and repeatable by domain experts that are not data scientists. SoBigData RI moves forward from the simple awareness of ethical and legal challenges in social mining to the development of concrete tools that operationalize ethics with value-sensitive design, incorporating values and norms for privacy protection, fairness, transparency, and pluralism. SoBigData RI is the result of two H2020 grants (g.a. n.654024 and 871042), and it is part of the ESFRI 2021 Roadmap. JF - 30th Italian Symposium on Advanced Database Systems (SEBD – Sistemi Evoluti per Basi di Dati) CY - Tirrenia, Pisa ER - TY - JOUR T1 - Explaining the difference between men’s and women’s football JF - PLOS ONE Y1 - 2021 A1 - Luca Pappalardo A1 - Alessio Rossi A1 - Michela Natilli A1 - Paolo Cintia ED - Constantinou, Anthony C. AB - Women’s football is gaining supporters and practitioners worldwide, raising questions about what the differences are with men’s football. While the two sports are often compared based on the players’ physical attributes, we analyze the spatio-temporal events during matches in the last World Cups to compare male and female teams based on their technical performance. We train an artificial intelligence model to recognize if a team is male or female based on variables that describe a match’s playing intensity, accuracy, and performance quality. Our model accurately distinguishes between men’s and women’s football, revealing crucial technical differences, which we investigate through the extraction of explanations from the classifier’s decisions. The differences between men’s and women’s football are rooted in play accuracy, the recovery time of ball possession, and the players’ performance quality. Our methodology may help journalists and fans understand what makes women’s football a distinct sport and coaches design tactics tailored to female teams. VL - 16 UR - https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0255407 JO - PLoS ONE ER - TY - JOUR T1 - Understanding eating choices among university students: A study using data from cafeteria cashiers’ transactions JF - Health Policy Y1 - 2021 A1 - Lorenzoni, Valentina A1 - Triulzi, Isotta A1 - Martinucci, Irene A1 - Toncelli, Letizia A1 - Michela Natilli A1 - Barale, Roberto A1 - Turchetti, Giuseppe VL - 125 ER - TY - CONF T1 - Analysis and Visualization of Performance Indicators in University Admission Tests T2 - Formal Methods. FM 2019 International Workshops Y1 - 2020 A1 - Michela Natilli A1 - Daniele Fadda A1 - S Rinzivillo A1 - Dino Pedreschi A1 - Licari, Federica ED - Sekerinski, Emil ED - Moreira, Nelma ED - Oliveira, José N. ED - Ratiu, Daniel ED - Riccardo Guidotti ED - Farrell, Marie ED - Luckcuck, Matt ED - Marmsoler, Diego ED - Campos, José ED - Astarte, Troy ED - Gonnord, Laure ED - Cerone, Antonio ED - Couto, Luis ED - Dongol, Brijesh ED - Kutrib, Martin ED - Monteiro, Pedro ED - Delmas, David AB - This paper presents an analytical platform for evaluation of the performance and anomaly detection of tests for admission to public universities in Italy. Each test is personalized for each student and is composed of a series of questions, classified on different domains (e.g. maths, science, logic, etc.). Since each test is unique for composition, it is crucial to guarantee a similar level of difficulty for all the tests in a session. For this reason, to each question, it is assigned a level of difficulty from a domain expert. Thus, the general difficultness of a test depends on the correct classification of each item. We propose two approaches to detect outliers. A visualization-based approach using dynamic filter and responsive visual widgets. A data mining approach to evaluate the performance of the different questions for five years. We used clustering to group the questions according to a set of performance indicators to provide labeling of the data-driven level of difficulty. The measured level is compared with the a priori assigned by experts. The misclassifications are then highlighted to the expert, who will be able to refine the question or the classification. Sequential pattern mining is used to check if biases are present in the composition of the tests and their performance. This analysis is meant to exclude overlaps or direct dependencies among questions. Analyzing co-occurrences we are able to state that the composition of each test is fair and uniform for all the students, even on several sessions. The analytical results are presented to the expert through a visual web application that loads the analytical data and indicators and composes an interactive dashboard. The user may explore the patterns and models extracted by filtering and changing thresholds and analytical parameters. JF - Formal Methods. FM 2019 International Workshops PB - Springer International Publishing CY - Cham SN - 978-3-030-54994-7 UR - https://link.springer.com/chapter/10.1007/978-3-030-54994-7_14 ER - TY - JOUR T1 - A Visual Analytics Platform to Measure Performance on University Entrance Tests (Discussion Paper) Y1 - 2019 A1 - Boncoraglio, Daniele A1 - Deri, Francesca A1 - Distefano, Francesco A1 - Daniele Fadda A1 - Filippi, Giorgio A1 - Forte, Giuseppe A1 - Licari, Federica A1 - Michela Natilli A1 - Dino Pedreschi A1 - S Rinzivillo ER - TY - CONF T1 - Exploring Students Eating Habits Through Individual Profiling and Clustering Analysis T2 - ECML PKDD 2018 Workshops Y1 - 2018 A1 - Michela Natilli A1 - Anna Monreale A1 - Riccardo Guidotti A1 - Luca Pappalardo JF - ECML PKDD 2018 Workshops PB - Springer ER - TY - JOUR T1 - Gastroesophageal reflux symptoms among Italian university students: epidemiology and dietary correlates using automatically recorded transactions JF - BMC gastroenterology Y1 - 2018 A1 - Martinucci, Irene A1 - Michela Natilli A1 - Lorenzoni, Valentina A1 - Luca Pappalardo A1 - Anna Monreale A1 - Turchetti, Giuseppe A1 - Dino Pedreschi A1 - Marchi, Santino A1 - Barale, Roberto A1 - de Bortoli, Nicola AB - Background: Gastroesophageal reflux disease (GERD) is one of the most common gastrointestinal disorders worldwide, with relevant impact on the quality of life and health care costs.The aim of our study is to assess the prevalence of GERD based on self-reported symptoms among university students in central Italy. The secondary aim is to evaluate lifestyle correlates, particularly eating habits, in GERD students using automatically recorded transactions through cashiers at university canteen. Methods: A web-survey was created and launched through an app, ad-hoc developed for an interactive exchange of information with students, including anthropometric data and lifestyle habits. Moreover, the web-survey allowed users a self-diagnosis of GERD through a simple questionnaire. As regard eating habits, detailed collection of meals consumed, including number and type of dishes, were automatically recorded through cashiers at the university canteen equipped with an automatic registration system. Results: We collected 3012 questionnaires. A total of 792 students (26.2% of the respondents) reported typical GERD symptoms occurring at least weekly. Female sex was more prevalent than male sex. In the set of students with GERD, the percentage of smokers was higher, and our results showed that when BMI tends to higher values the percentage of students with GERD tends to increase. When evaluating correlates with diet, we found, among all users, a lower frequency of legumes choice in GERD students and, among frequent users, a lower frequency of choice of pasta and rice in GERD students. Discussion: The results of our study are in line with the values reported in the literature. Nowadays, GERD is a common problem in our communities, and can potentially lead to serious medical complications; the economic burden involved in the diagnostic and therapeutic management of the disease has a relevant impact on healthcare costs. Conclusions: To our knowledge, this is the first study evaluating the prevalence of typical GERD–related symptoms in a young population of University students in Italy. Considering the young age of enrolled subjects, our prevalence rate, relatively high compared to the usual estimates, could represent a further negative factor for the future economic sustainability of the healthcare system. Keywords: Gastroesophageal reflux disease, GERD, Heartburn, Regurgitation, Diet, Prevalence, University students VL - 18 UR - https://bmcgastroenterol.biomedcentral.com/articles/10.1186/s12876-018-0832-9 ER - TY - JOUR T1 - Wine and Food Tourism First European Conference JF - Edizioni ETS Pisa Y1 - 2012 A1 - Romano, Maria Francesca A1 - Michela Natilli ER - TY - BOOK T1 - Dinamiche di impoverimento. Meccanismi, traiettorie ed effetti in un contesto locale Y1 - 2011 A1 - Tomei, Gabriele A1 - Michela Natilli PB - Carocci Editore ER - TY - CONF T1 - The impact of wine and food tourism in Italy: an analysis of official statistical data at province level T2 - First European Conference on Wine and Food Tourism Y1 - 2011 A1 - Michela Natilli A1 - Romano, Maria Francesca JF - First European Conference on Wine and Food Tourism ER - TY - CONF T1 - The language of tourists in a wine and food blog T2 - First European Conference on Wine and Food Tourism Y1 - 2011 A1 - Pavone, Pasquale A1 - Michela Natilli A1 - Romano, Maria Francesca JF - First European Conference on Wine and Food Tourism ER - TY - JOUR T1 - Measuring the effectiveness of homeopathic care through objective and shared indicators JF - Homeopathy Y1 - 2011 A1 - Leone, Laura A1 - Marchitiello, Maria A1 - Michela Natilli A1 - Romano, Maria Francesca VL - 100 ER - TY - JOUR T1 - Stiramenti identitari. Strategie di integrazione degli strannieri nella provincia di Massa Carrara tra appartenenza etnica ed esperienza transnazionale Y1 - 2011 A1 - Tomei, Gabriele A1 - Paletti, F A1 - Michela Natilli ER - TY - CONF T1 - Poverty as a Social Condition: a Case Study on a Small Municipality in Tuscany T2 - Global Recession: Regional Impacts on Housing, Jobs, Health and Wellbeing Y1 - 2009 A1 - Tomei, Gabriele A1 - Michela Natilli JF - Global Recession: Regional Impacts on Housing, Jobs, Health and Wellbeing PB - SEAFORD ER - TY - JOUR T1 - Wine tourism in Italy: New profiles, styles of consumption, ways of touring JF - Turizam: međunarodni znanstveno-stručni časopis Y1 - 2009 A1 - Romano, Maria Francesca A1 - Michela Natilli VL - 57 ER - TY - CONF T1 - Comparative indicators of regional poverty and deprivation: Poland versus EU-15 Member States T2 - conference Comparative Economic Analysis of Households‟ Behaviour (CEAHB): Old and New EU Members, Warsaw University Y1 - 2005 A1 - Betti, Gianni A1 - Mulas, Anna A1 - Michela Natilli A1 - Neri, Laura A1 - Verma, Vijay JF - conference Comparative Economic Analysis of Households‟ Behaviour (CEAHB): Old and New EU Members, Warsaw University ER - TY - ABST T1 - Indicators of social exclusion and poverty in Europe’s regions Y1 - 2005 A1 - Verma, Vijay A1 - Betti, Gianni A1 - Michela Natilli A1 - Lemmi, Achille ER - TY - CONF T1 - Personal income in the gross and net forms: applications of the Siena Micro-Simulation Model (SM2) T2 - conference of the Società Italiana di Economia, Demografia e Statistica (SIEDS), Campobasso Y1 - 2003 A1 - Verma, V A1 - Betti, G A1 - Ballini, F A1 - Michela Natilli A1 - Galgani, S JF - conference of the Società Italiana di Economia, Demografia e Statistica (SIEDS), Campobasso ER -