Ivan Donadello

636 citations
34 papers · 377 · h-index 12

Impact in

    • Artificial Intelligence in Healthcare and Education
    • Explainable Artificial Intelligence (XAI)
    • Topic Modeling
    • Sentiment Analysis and Opinion Mining
    • Machine Learning in Healthcare

Papers in

Ivan Donadello

29 papers receiving 367 citations

Peers

Ivan Donadello
Comparison fields: 5 of 81
  • Health Informatics 33
  • Artificial Intelligence 242
  • Management Information Systems 32
  • Safety Research 24
  • Applied Psychology 12
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Citations per year

Countries citing papers authored by Ivan Donadello

Since Specialization
Citations

This map shows the geographic impact of Ivan Donadello'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 Ivan Donadello with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ivan Donadello more than expected).

Fields of papers citing papers by Ivan Donadello

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ivan Donadello. 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 Ivan Donadello. The network helps show where Ivan Donadello may publish in the future.

Co-authors

The 25 scholars most cited alongside Ivan Donadello, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Ivan Donadello Line = papers co-authored together Ivan Donadello links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202279
2 202050
3 202241
4 202438
5 201723
6 201916
7 201915
8
Persuasive Explanation of Reasoning Inferences on Dietary Data.
201912
9 201611
10 202011
11 202311
12 201511
13 20169
14 20226
15 20226
16 20226
17 20245
18 20215
19 20234
20 20184

About Ivan Donadello

Ivan Donadello is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Management Information Systems, Information Systems and Molecular Biology, having authored 34 papers that have together received 377 indexed citations. Recurring topics across this work include Topic Modeling (7 papers), Explainable Artificial Intelligence (XAI) (7 papers), Business Process Modeling and Analysis (5 papers), Service-Oriented Architecture and Web Services (5 papers), Semantic Web and Ontologies (4 papers), Multimodal Machine Learning Applications (3 papers), Advanced Image and Video Retrieval Techniques (3 papers) and Image Retrieval and Classification Techniques (3 papers). The work is most often cited by research in Health Informatics (33 citations), Artificial Intelligence (242 citations), Management Information Systems (32 citations), Safety Research (24 citations) and Applied Psychology (12 citations). Ivan Donadello has collaborated with scholars based in Italy, United Kingdom and France. Frequent co-authors include Mauro Dragoni, Luciano Serafini, Claudio Eccher, Erik Cambria, Artur d’Avila Garcez, Fabrizio Maria Maggi, Chiara Di Francescomarino, B.J. Wagner, Raja Chatila and Natalia Díaz-Rodríguez. Their work appears in journals such as Information Systems, IEEE Intelligent Systems, Data Intelligence, Frontiers in Psychology and Artificial Intelligence in Medicine.

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.

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