Iacopo Vagliano

Orcid: 0000-0002-3066-9464

Affiliations:
  • Christian Albrechts University of Kiel, Department of Computer Science, Germany
  • Polytechnic University of Turin, Dept. of Control and Computer Engineering, Italy


According to our database1, Iacopo Vagliano authored at least 36 papers between 2013 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

Online presence:

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Bibliography

2023
Prognostic models of in-hospital mortality of intensive care patients using neural representation of unstructured text: A systematic review and critical appraisal.
J. Biomed. Informatics, October, 2023

Automated identification of patient subgroups: A case-study on mortality of COVID-19 patients admitted to the ICU.
Comput. Biol. Medicine, September, 2023

Lifelong learning on evolving graphs under the constraints of imbalanced classes and new classes.
Neural Networks, July, 2023

Leveraging Multi-Word Concepts to Predict Acute Kidney Injury in Intensive Care.
Proceedings of the Healthcare Transformation with Informatics and Artificial Intelligence, 2023

Autoencoder-Based Prediction of ICU Clinical Codes.
Proceedings of the Artificial Intelligence in Medicine, 2023

Soft-Prompt Tuning to Predict Lung Cancer Using Primary Care Free-Text Dutch Medical Notes.
Proceedings of the Artificial Intelligence in Medicine, 2023

2022
Recommendations for item set completion: on the semantics of item co-occurrence with data sparsity, input size, and input modalities.
Inf. Retr. J., 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.
Int. J. Medical Informatics, 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.
Int. J. Medical Informatics, 2022

External Validation and Transportability of Models to Predict Acute Kidney Injury in the Intensive Care Unit.
Proceedings of the Advances in Informatics, Management and Technology in Healthcare, 2022

2021
Lifelong Learning in Evolving Graphs with Limited Labeled Data and Unseen Class Detection.
CoRR, 2021

Interpretable and Continuous Prediction of Acute Kidney Injury in the Intensive Care.
Proceedings of the Public Health and Informatics, 2021

Machine Learning, Clinical Notes and Knowledge Graphs for Early Prediction of Acute Kidney Injury in the Intensive Care.
Proceedings of the Informatics and Technology in Clinical Care and Public Health, 2021

2020
Incremental Training of Graph Neural Networks on Temporal Graphs under Distribution Shift.
CoRR, 2020

2019
Can Graph Neural Networks Go "Online"? An Analysis of Pretraining and Inference.
CoRR, 2019

Training Researchers with the MOVING Platform.
Proceedings of the MultiMedia Modeling - 25th International Conference, 2019

Analyzing the Evolution of Linked Vocabularies.
Proceedings of the Web Engineering - 19th International Conference, 2019

Recommending Multimedia Educational Resources on the MOVING Platform.
Proceedings of the 8th International Workshop on Bibliometric-enhanced Information Retrieval (BIR 2019) co-located with the 41st European Conference on Information Retrieval (ECIR 2019), 2019

2018
Open Innovation in the Big Data Era With the MOVING Platform.
IEEE Multim., 2018

Multi-Modal Adversarial Autoencoders for Recommendations of Citations and Subject Labels.
Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization, 2018

Using Adversarial Autoencoders for Multi-Modal Automatic Playlist Continuation.
Proceedings of the ACM Recommender Systems Challenge, 2018

Analyzing the Evolution of Vocabulary Terms and Their Impact on the LOD Cloud.
Proceedings of the Semantic Web - 15th International Conference, 2018

2017
Content Recommendation Through Linked Data.
PhD thesis, 2017

Allied: A Framework for Executing Linked Data-Based Recommendation Algorithms.
Int. J. Semantic Web Inf. Syst., 2017

Content Recommendation through Semantic Annotation of User Reviews and Linked Data - An Extended Technical Report.
CoRR, 2017

SemRevRec: A Recommender System based on User Reviews and Linked Data.
Proceedings of the Poster Track of the 11th ACM Conference on Recommender Systems (RecSys 2017), 2017

Content Recommendation through Semantic Annotation of User Reviews and Linked Data.
Proceedings of the Knowledge Capture Conference, 2017

Tool Integration in the Aerospace Domain: A Case Study.
Proceedings of the 41st IEEE Annual Computer Software and Applications Conference, 2017

Serendipitous Recommendations Through Ontology-Based Contextual Pre-filtering.
Proceedings of the Beyond Databases, Architectures and Structures. Towards Efficient Solutions for Data Analysis and Knowledge Representation, 2017

2016
ReDyAl: A Dynamic Recommendation Algorithm based on Linked Data.
Proceedings of the 3rd Workshop on New Trends in Content-Based Recommender Systems co-located with ACM Conference on Recommender Systems (RecSys 2016), 2016

An Ontology-based Contextual Pre-filtering Technique for Recommender Systems.
Proceedings of the 2016 Federated Conference on Computer Science and Information Systems, 2016

2015
Semantic Annotation and Classification in Practice.
IT Prof., 2015

A systematic literature review of Linked Data-based recommender systems.
Concurr. Comput. Pract. Exp., 2015

DBpedia Mobile Explorer.
Proceedings of the 1st IEEE International Forum on Research and Technologies for Society and Industry Leveraging a better tomorrow, 2015

2014
Linked Data-Driven Smart Spaces.
Proceedings of the Internet of Things, Smart Spaces, and Next Generation Networks and Systems, 2014

2013
Assisted Policy Management for SPARQL Endpoints Access Control.
Proceedings of the ISWC 2013 Posters & Demonstrations Track, 2013


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