Assisted Policy Management for SPARQL Endpoints Access Control. - Luca Costabello; Serena Villata; Iacopo Vagliano; Fabien Gandon (ISWC (Posters & Demos), 2013)

Linked Data-Driven Smart Spaces. - Oscar Rodriguez Rocha; Cristhian Figueroa; Iacopo Vagliano; Boris Moltchanov (NEW2AN, 2014)

DBpedia Mobile Explorer. - Iacopo Vagliano; Marco Marengo; Maurizio Morisio (RTSI, 2015)

A systematic literature review of Linked Data-based recommender systems. - Cristhian Figueroa; Iacopo Vagliano; Oscar Rodriguez Rocha; Maurizio Morisio (Concurr. Comput. Pract. Exp., 2015)

Semantic Annotation and Classification in Practice. - Oscar Rodriguez Rocha; Iacopo Vagliano; Cristhian Figueroa; Federico Cairo; Giuseppe Futia; Carlo Alberto Licciardi; Marco Marengo; Federico Morando (IT Prof., 2015)

An Ontology-based Contextual Pre-filtering Technique for Recommender Systems. - Aleksandra Karpus; Iacopo Vagliano; Krzysztof Goczyla; Maurizio Morisio (FedCSIS, 2016)

ReDyAl: A Dynamic Recommendation Algorithm based on Linked Data. - Iacopo Vagliano; Cristhian Figueroa; Oscar Rodriguez Rocha; Marco Torchiano; Catherine Faron-Zucker; Maurizio Morisio (CBRecSys@RecSys, 2016)

Serendipitous Recommendations Through Ontology-Based Contextual Pre-filtering. - Aleksandra Karpus; Iacopo Vagliano; Krzysztof Goczyla (BDAS, 2017)

Tool Integration in the Aerospace Domain: A Case Study. - Iacopo Vagliano; Davide Ferretto; Eugenio Brusa; Maurizio Morisio; Laura Valacca (COMPSAC (1), 2017)

Content Recommendation through Semantic Annotation of User Reviews and Linked Data. - Iacopo Vagliano; Diego Monti; Ansgar Scherp; Maurizio Morisio (K-CAP, 2017)

SemRevRec: A Recommender System based on User Reviews and Linked Data. - Iacopo Vagliano; Diego Monti; Maurizio Morisio (RecSys Posters, 2017)

Content Recommendation through Semantic Annotation of User Reviews and Linked Data - An Extended Technical Report. - Iacopo Vagliano; Diego Monti; Ansgar Scherp; Maurizio Morisio (CoRR, 2017)

Allied: A Framework for Executing Linked Data-Based Recommendation Algorithms. - Cristhian Figueroa; Iacopo Vagliano; Oscar Rodriguez Rocha; Marco Torchiano; Catherine Faron-Zucker; Juan Carlos Corrales; Maurizio Morisio (Int. J. Semantic Web Inf. Syst., 2017)

Content Recommendation Through Linked Data. - Iacopo Vagliano (2017)

Analyzing the Evolution of Vocabulary Terms and Their Impact on the LOD Cloud. - Mohammad Abdel-Qader; Ansgar Scherp; Iacopo Vagliano (ESWC, 2018)

Using Adversarial Autoencoders for Multi-Modal Automatic Playlist Continuation. - Iacopo Vagliano; Lukas Galke; Florian Mai; Ansgar Scherp (RecSys Challenge, 2018)

Multi-Modal Adversarial Autoencoders for Recommendations of Citations and Subject Labels. - Lukas Galke; Florian Mai; Iacopo Vagliano; Ansgar Scherp (UMAP, 2018)

Open Innovation in the Big Data Era With the MOVING Platform. - Iacopo Vagliano; Franziska Günther; Matthias Heinz; Aitor Apaolaza; Irina Bienia; Gert Breitfuss; Till Blume; Chrysa Collyda; Angela Fessl; Sebastian Gottfried; Peter Hasitschka; Jasmin Kellermann; et al. (IEEE Multim., 2018)

Recommending Multimedia Educational Resources on the MOVING Platform. - Iacopo Vagliano; Sibgha Nazir (BIR@ECIR, 2019)

Analyzing the Evolution of Linked Vocabularies. - Mohammad Abdel-Qader; Iacopo Vagliano; Ansgar Scherp (ICWE, 2019)

Training Researchers with the MOVING Platform. - Iacopo Vagliano; Angela Fessl; Franziska Günther; Thomas Köhler 001; Vasileios Mezaris; Ahmed Saleh 003; Ansgar Scherp; Ilija Simic (MMM (2), 2019)

Can Graph Neural Networks Go "Online"? An Analysis of Pretraining and Inference. - Lukas Galke; Iacopo Vagliano; Ansgar Scherp (CoRR, 2019)

Statistics of the Network of Linked Vocabularies. - Mohammad Abdel-Qader; Iacopo Vagliano; Ansgar Scherp (Zenodo, 2019)

Incremental Training of Graph Neural Networks on Temporal Graphs under Distribution Shift. - Lukas Galke; Iacopo Vagliano; Ansgar Scherp (CoRR, 2020)

Machine Learning, Clinical Notes and Knowledge Graphs for Early Prediction of Acute Kidney Injury in the Intensive Care. - Iacopo Vagliano; Wei-Hsiang Hsu; Martijn C. Schut (ICIMTH, 2021)

Interpretable and Continuous Prediction of Acute Kidney Injury in the Intensive Care. - Iacopo Vagliano; Oleksandra Lvova; Martijn C. Schut (MIE, 2021)

Lifelong Learning in Evolving Graphs with Limited Labeled Data and Unseen Class Detection. - Lukas Galke; Iacopo Vagliano; Benedikt Franke; Tobias Zielke; Ansgar Scherp (CoRR, 2021)

External Validation and Transportability of Models to Predict Acute Kidney Injury in the Intensive Care Unit. - Iacopo Vagliano; Carmen Byrne Salsas; Tina Wünn; Martijn C. Schut (ICIMTH, 2022)

Can we reliably automate clinical prognostic modelling? A retrospective cohort study for ICU triage prediction of in-hospital mortality of COVID-19 patients in the Netherlands. - Iacopo Vagliano; Sylvia Brinkman; Ameen Abu-Hanna; M. Sesmu Arbous; Dave A. Dongelmans; Paul W. G. Elbers; Dylan W. De Lange; Mihaela van der Schaar; Nicolette F. de Keizer; Martijn C. Schut (Int. J. Medical Informatics, 2022)

Assess and validate predictive performance of models for in-hospital mortality in COVID-19 patients: A retrospective cohort study in the Netherlands comparing the value of registry data with high-granular electronic health records. - Iacopo Vagliano; Martijn C. Schut; Ameen Abu-Hanna; Dave A. Dongelmans; Dylan W. De Lange; Diederik Gommers; Olaf L. Cremer; Rob J. Bosman; Sander Rigter; Evert-Jan Wils; Tim Frenzel; Remko de Jong; et al. (Int. J. Medical Informatics, 2022)

Recommendations for item set completion: on the semantics of item co-occurrence with data sparsity, input size, and input modalities. - Iacopo Vagliano; Lukas Galke; Ansgar Scherp (Inf. Retr. J., 2022)

Soft-Prompt Tuning to Predict Lung Cancer Using Primary Care Free-Text Dutch Medical Notes. - Auke Elfrink; Iacopo Vagliano; Ameen Abu-Hanna; Iacer Calixto (AIME, 2023)

Autoencoder-Based Prediction of ICU Clinical Codes. - Tsvetan R. Yordanov; Ameen Abu-Hanna; Anita C. J. Ravelli; Iacopo Vagliano (AIME, 2023)

Leveraging Multi-Word Concepts to Predict Acute Kidney Injury in Intensive Care. - Lorenzo Brancato; Iacer Calixto; Ameen Abu-Hanna; Iacopo Vagliano (ICIMTH, 2023)

Lifelong learning on evolving graphs under the constraints of imbalanced classes and new classes. - Lukas Galke; Iacopo Vagliano; Benedikt Franke; Tobias Zielke; Marcel Hoffmann 002; Ansgar Scherp (Neural Networks, 2023)

Automated identification of patient subgroups: A case-study on mortality of COVID-19 patients admitted to the ICU. - Iacopo Vagliano; Maurice Y. Kingma; Dave A. Dongelmans; Dylan W. De Lange; Nicolette F. de Keizer; Martijn C. Schut (Comput. Biol. Medicine, 2023)

Prognostic models of in-hospital mortality of intensive care patients using neural representation of unstructured text: A systematic review and critical appraisal. - Iacopo Vagliano; Noman Dormosh; Miguel Rios; Torec T. Luik; T. M. Buonocore; Paul W. G. Elbers; Dave A. Dongelmans; Martijn C. Schut; Ameen Abu-Hanna (J. Biomed. Informatics, 2023)

Large language models versus static word embeddings to predict Acute Kidney Injury in the Intensive Care Unit: Does context matter? - Rick van Slobbe; Drahomira Herrmannova; Elia Lima-Walton; Ameen Abu-Hanna; Iacopo Vagliano (SLM4Health@AIME, 2025)

Determinants influencing medication-related alert handling in the electronic health record: A systematic review and meta-analysis. - Kimmy Raven; Jiaxu Zhang; Iacopo Vagliano; Monique W. M. Jaspers; Linda W. Peute; Stephanie Medlock (Int. J. Medical Informatics, 2025)

Multimodal convolutional neural networks for the prediction of acute kidney injury in the intensive care. - Rick van Slobbe; Drahomira Herrmannova; Dijs Johan Boeke; Elia Lima-Walton; Ameen Abu-Hanna; Iacopo Vagliano (Int. J. Medical Informatics, 2025)