Elpida Keravnou

1.0k total citations
42 papers, 577 citations indexed

About

Elpida Keravnou is a scholar working on Artificial Intelligence, Molecular Biology and Information Systems. According to data from OpenAlex, Elpida Keravnou has authored 42 papers receiving a total of 577 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Artificial Intelligence, 10 papers in Molecular Biology and 9 papers in Information Systems. Recurrent topics in Elpida Keravnou's work include AI-based Problem Solving and Planning (20 papers), Biomedical Text Mining and Ontologies (10 papers) and Semantic Web and Ontologies (9 papers). Elpida Keravnou is often cited by papers focused on AI-based Problem Solving and Planning (20 papers), Biomedical Text Mining and Ontologies (10 papers) and Semantic Web and Ontologies (9 papers). Elpida Keravnou collaborates with scholars based in Cyprus, United Kingdom and Italy. Elpida Keravnou's co-authors include John Washbrook, Athena Stassopoulou, Leslie Main Johnson, Amar K. Das, Carlo Combi, Giuseppe Pozzi, Klaus-Peter Adlassnig, Lucia Sacchi, Arianna Dagliati and Riccardo Bellazzi and has published in prestigious journals such as Computer Physics Communications, Knowledge-Based Systems and Computer Methods and Programs in Biomedicine.

In The Last Decade

Elpida Keravnou

41 papers receiving 522 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Elpida Keravnou Cyprus 15 384 117 114 94 94 42 577
Janice R. Boughton Australia 4 429 1.1× 135 1.2× 64 0.6× 39 0.4× 41 0.4× 5 574
Yuni Xia United States 12 191 0.5× 100 0.9× 29 0.3× 82 0.9× 126 1.3× 25 363
Daby Sow United States 14 235 0.6× 96 0.8× 52 0.5× 176 1.9× 101 1.1× 58 693
Gonzalo Ramos-Jiménez Spain 9 426 1.1× 48 0.4× 57 0.5× 83 0.9× 64 0.7× 11 552
Fabrizio Riguzzi Italy 15 538 1.4× 111 0.9× 27 0.2× 94 1.0× 49 0.5× 108 717
Salah Ud Din China 14 475 1.2× 79 0.7× 46 0.4× 91 1.0× 95 1.0× 25 905
Manabu Nii Japan 13 545 1.4× 73 0.6× 25 0.2× 40 0.4× 39 0.4× 111 815
I C G Campbell 8 427 1.1× 47 0.4× 82 0.7× 24 0.3× 53 0.6× 10 667
Nahla Barakat Egypt 8 443 1.2× 134 1.1× 38 0.3× 19 0.2× 26 0.3× 21 701
Cindy Marling United States 12 257 0.7× 55 0.5× 50 0.4× 16 0.2× 41 0.4× 26 731

Countries citing papers authored by Elpida Keravnou

Since Specialization
Citations

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

Fields of papers citing papers by Elpida Keravnou

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Elpida Keravnou

This figure shows the co-authorship network connecting the top 25 collaborators of Elpida Keravnou. A scholar is included among the top collaborators of Elpida Keravnou based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Elpida Keravnou. Elpida Keravnou is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Dagliati, Arianna, et al.. (2018). Incorporating repeating temporal association rules in Naïve Bayes classifiers for coronary heart disease diagnosis. Journal of Biomedical Informatics. 81. 74–82. 24 indexed citations
2.
3.
Miksch, Silvia, Jim Hunter, & Elpida Keravnou. (2005). Artificial Intelligence in Medicine: 10th Conference on Artificial Intelligence in Medicine, AIME 2005, Aberdeen, UK, July 23-27, 2005, Proceedings (Lecture ... / Lecture Notes in Artificial Intelligence). Springer eBooks. 2 indexed citations
4.
Dojat, Michel, Elpida Keravnou, & Pedro Barahona. (2003). Artificial Intelligence in Medicine: 9th Conference on Artificial Intelligence in Medicine in Europe, Aime 2003, Protaras, Cyprus, October 18-22, 2003, Proceedings (Lecture Notes in Computer Science, 2780.). Springer eBooks. 3 indexed citations
5.
Keravnou, Elpida & John Washbrook. (2001). Abductive Diagnosis Using Time‐Objects: Criteria for the Evaluation of Solutions. Computational Intelligence. 17(1). 87–131. 3 indexed citations
6.
Lavrač, Nada, Igor Kononenko, Elpida Keravnou, Matjaž Kukar, & Blaž Zupan. (1998). Intelligent data analysis for medical diagnosisc using machine learning and temporal abstraction. AI Communications. 11(3). 191–218. 17 indexed citations
7.
Christodoulou, Eleni & Elpida Keravnou. (1998). Metareasoning and meta-level learning in a hybrid knowledge-based architecture. Artificial Intelligence in Medicine. 14(1-2). 53–81. 5 indexed citations
8.
Keravnou, Elpida, Catherine Garbay, Robert Baud, & Jeremy C Wyatt. (1997). Proceedings of the 6th Conference on Artificial Intelligence in Medicine in Europe. 6 indexed citations
9.
Keravnou, Elpida. (1997). Artificial intelligence in medicine : 6th Conference on Artificial Intelligence in Medicine Europe, AIME '97, Grenoble, France, March 23-26, 1997 : proceedings. Springer eBooks. 2 indexed citations
10.
Keravnou, Elpida. (1996). Temporal diagnostic reasoning based on time-objects. Artificial Intelligence in Medicine. 8(3). 235–265. 20 indexed citations
11.
Keravnou, Elpida, et al.. (1994). Modelling diagnostic skills in the domain of skeletal dysplasias. Computer Methods and Programs in Biomedicine. 45(4). 239–260. 8 indexed citations
12.
Keravnou, Elpida, et al.. (1993). Towards competent information acquisition interactions between an expert system and its user. Knowledge-Based Systems. 6(3). 141–156. 2 indexed citations
13.
Keravnou, Elpida. (1992). Deep Models for Medical Knowledge Engineering. Elsevier eBooks. 17 indexed citations
14.
Keravnou, Elpida, et al.. (1992). Background knowledge in diagnosis. Artificial Intelligence in Medicine. 4(4). 263–279. 6 indexed citations
15.
Keravnou, Elpida & John Washbrook. (1990). A temporal reasoning framework used in the diagnosis of skeletal dysplasias. Artificial Intelligence in Medicine. 2(5). 239–265. 29 indexed citations
16.
Washbrook, John & Elpida Keravnou. (1990). Making deepness explicit. Artificial Intelligence in Medicine. 2(3). 129–134. 6 indexed citations
17.
Keravnou, Elpida & John Washbrook. (1989). What is a deep expert system? An analysis of the architectural requirements of second-generation expert systems. The Knowledge Engineering Review. 4(3). 205–233. 28 indexed citations
18.
Keravnou, Elpida & Leslie Main Johnson. (1989). Towards a generalized model of diagnostic behaviour. Knowledge-Based Systems. 2(3). 165–177. 5 indexed citations
19.
Keravnou, Elpida, et al.. (1988). Expert systems architectures. Kogan Page eBooks. 9 indexed citations
20.
Keravnou, Elpida, et al.. (1985). Expert Systems Technology: A Guide. 15 indexed citations

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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