Giulia Vilone
Impact in
- Health Informatics top 1%
- Artificial Intelligence in Healthcare and Education
- Artificial Intelligence top 5%
- Explainable Artificial Intelligence (XAI)
- Adversarial Robustness in Machine Learning
- Machine Learning in Healthcare
- Machine Learning and Data Classification
- Topic Modeling
Papers in
-
- Explainable Artificial Intelligence (XAI) 5
- Adversarial Robustness in Machine Learning 2
- Machine Learning and Data Classification 2
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- Effects and risks of endocrine disrupting chemicals 3
- Co-authors
- Luca Longo (5 shared papers)Cian O’Mahony (3 shared papers)Christina Cowan‐Ellsberry (1 shared paper)Jon A. Arnot (1 shared paper)Sean M. Hays (1 shared paper)Fanny Héraud (1 shared paper)Daniel Q. Naiman (1 shared paper)John N. Westgate (1 shared paper)
- Journals
- Information Fusion (1 paper)Journal of Toxicology and Environmental Health Part B (1 paper)Journal of Exposure Science & Environmental Epidemiology (1 paper)Food Additives & Contaminants Part A (1 paper)Frontiers in Artificial Intelligence (1 paper)
- Partner nations
- IrelandUnited StatesCanada
In The Last Decade
Giulia Vilone
11 papers receiving 503 citations
Giulia Vilone's Hit Papers
Peers
Comparison fields: 5 of 112
- Health Informatics 83
- Artificial Intelligence 325
- Safety Research 53
- Chemical Health and Safety 3
- Information Systems and Management 29
Countries citing papers authored by Giulia Vilone
This map shows the geographic impact of Giulia Vilone's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Giulia Vilone with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Giulia Vilone more than expected).
Fields of papers citing papers by Giulia Vilone
This network shows the impact of papers produced by Giulia Vilone. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Giulia Vilone. The network helps show where Giulia Vilone may publish in the future.
Co-authors
The 12 scholars most cited alongside Giulia Vilone, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Notions of explainability and evaluation approaches for explainable artificial intelligence Hit paper breakdown → | 2021 | 329 |
| 2 | 2021 | 89 | |
| 3 | 2020 | 42 | |
| 4 | 2021 | 15 | |
| 5 | 2017 | 13 | |
| 6 | 2018 | 11 | |
| 7 | 2014 | 8 | |
| 8 | 2021 | 6 | |
| 9 | 2020 | 5 | |
| 10 | 2021 | 4 | |
| 11 | 2013 | 2 |
About Giulia Vilone
Giulia Vilone is a scholar working on Artificial Intelligence, Health, Toxicology and Mutagenesis, Health Informatics, Public Health, Environmental and Occupational Health and Plant Science, having authored 11 papers that have together received 524 indexed citations. Recurring topics across this work include Explainable Artificial Intelligence (XAI) (5 papers), Effects and risks of endocrine disrupting chemicals (3 papers), Adversarial Robustness in Machine Learning (2 papers), Nutritional Studies and Diet (2 papers), Pesticide Exposure and Toxicity (2 papers), Artificial Intelligence in Healthcare and Education (2 papers), Machine Learning and Data Classification (2 papers) and Consumer Attitudes and Food Labeling (2 papers). The work is most often cited by research in Health Informatics (83 citations), Artificial Intelligence (325 citations), Safety Research (53 citations), Chemical Health and Safety (3 citations) and Information Systems and Management (29 citations). Giulia Vilone has collaborated with scholars based in Ireland, United States and Canada. Frequent co-authors include Luca Longo, Cian O’Mahony, Christina Cowan‐Ellsberry, Jon A. Arnot, Sean M. Hays, Fanny Héraud, Daniel Q. Naiman, John N. Westgate, Lesa L. Aylward and Carol J. Burns. Their work appears in journals such as Information Fusion, Journal of Toxicology and Environmental Health Part B, Journal of Exposure Science & Environmental Epidemiology, Food Additives & Contaminants Part A and Frontiers in Artificial Intelligence.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.