José M. Juárez

911 total citations
56 papers, 481 citations indexed

About

José M. Juárez is a scholar working on Artificial Intelligence, Computer Networks and Communications and Health Information Management. According to data from OpenAlex, José M. Juárez has authored 56 papers receiving a total of 481 indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Artificial Intelligence, 13 papers in Computer Networks and Communications and 10 papers in Health Information Management. Recurrent topics in José M. Juárez's work include Semantic Web and Ontologies (17 papers), AI-based Problem Solving and Planning (14 papers) and Biomedical Text Mining and Ontologies (9 papers). José M. Juárez is often cited by papers focused on Semantic Web and Ontologies (17 papers), AI-based Problem Solving and Planning (14 papers) and Biomedical Text Mining and Ontologies (9 papers). José M. Juárez collaborates with scholars based in Spain, Italy and United Kingdom. José M. Juárez's co-authors include Manuel Campos, R. Marı́n, José Palma, Carlo Combi, Fernando Jiménez, Antonio Morales, Gracia Sánchez, Barbara Oliboni, Francisco Palácios and Haomin Li and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Expert Systems with Applications.

In The Last Decade

José M. Juárez

49 papers receiving 467 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
José M. Juárez Spain 14 252 86 78 73 62 56 481
David Riaño Spain 12 216 0.9× 115 1.3× 56 0.7× 118 1.6× 41 0.7× 50 440
Arjen Hommersom Netherlands 12 199 0.8× 49 0.6× 58 0.7× 52 0.7× 15 0.2× 49 424
Barbara Oliboni Italy 13 151 0.6× 33 0.4× 134 1.7× 54 0.7× 119 1.9× 39 383
R. Marı́n Spain 15 327 1.3× 51 0.6× 74 0.9× 56 0.8× 34 0.5× 63 620
Giorgio Leonardi Italy 9 187 0.7× 32 0.4× 89 1.1× 53 0.7× 153 2.5× 31 339
Muhammad Ayaz Malaysia 7 110 0.4× 86 1.0× 138 1.8× 35 0.5× 18 0.3× 12 432
Francisca Nonyelum Ogwueleka Nigeria 9 252 1.0× 152 1.8× 136 1.7× 25 0.3× 44 0.7× 22 588
Juan Fernández-Olivares Spain 10 179 0.7× 20 0.2× 47 0.6× 30 0.4× 52 0.8× 34 291
Vassilis Koutkias Greece 19 167 0.7× 203 2.4× 129 1.7× 106 1.5× 42 0.7× 82 1.0k
A. Carlisle Scott United States 7 341 1.4× 59 0.7× 113 1.4× 66 0.9× 45 0.7× 11 570

Countries citing papers authored by José M. Juárez

Since Specialization
Citations

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

Fields of papers citing papers by José M. Juárez

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by José M. Juárez. 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 José M. Juárez. The network helps show where José M. Juárez may publish in the future.

Co-authorship network of co-authors of José M. Juárez

This figure shows the co-authorship network connecting the top 25 collaborators of José M. Juárez. A scholar is included among the top collaborators of José M. Juárez 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 José M. Juárez. José M. Juárez 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.
Campos, Manuel, et al.. (2024). Spatiotemporal Data Modelling for Epidemiological Research in Hospitals. IEEE Journal of Biomedical and Health Informatics. 28(10). 6280–6291.
2.
Juárez, José M., et al.. (2024). Subgroups: A Python library for Subgroup Discovery. SoftwareX. 28. 101895–101895.
3.
Campos, Manuel, et al.. (2024). Surprising and novel multivariate sequential patterns using odds ratio for temporal evolution in healthcare. BMC Medical Informatics and Decision Making. 24(1). 165–165.
4.
Juárez, José M., et al.. (2023). VLSD—An Efficient Subgroup Discovery Algorithm Based on Equivalence Classes and Optimistic Estimate. Algorithms. 16(6). 274–274. 1 indexed citations
5.
Campos, Manuel, et al.. (2023). The use of networks in spatial and temporal computational models for outbreak spread in epidemiology: A systematic review. Journal of Biomedical Informatics. 143. 104422–104422. 10 indexed citations
6.
Morales, Antonio, et al.. (2023). Meaningful time-related aspects of alerts in Clinical Decision Support Systems. A unified framework. Journal of Biomedical Informatics. 143. 104397–104397.
7.
Juárez, José M., et al.. (2022). Handling Time Constraints in Infection Clinical Pathways Using openEHR TP. Studies in health technology and informatics. 290. 7–11. 2 indexed citations
8.
Juárez, José M., et al.. (2021). A methodology based on Trace-based clustering for patient phenotyping. Knowledge-Based Systems. 232. 107469–107469. 5 indexed citations
9.
Juárez, José M., et al.. (2020). Fenómenos emergentes relacionados con las amenazas híbridas y respuesta de la Unión Europea. Dialnet (Universidad de la Rioja). 27–42.
10.
Juárez, José M., et al.. (2020). Comprehensive analysis of rule formalisms to represent clinical guidelines: Selection criteria and case study on antibiotic clinical guidelines. Artificial Intelligence in Medicine. 103. 101741–101741. 13 indexed citations
11.
Campos, Manuel, Fernando Jiménez, Gracia Sánchez, et al.. (2019). A methodology based on multiple criteria decision analysis for combining antibiotics in empirical therapy. Artificial Intelligence in Medicine. 102. 101751–101751. 4 indexed citations
12.
Morales, Antonio, et al.. (2018). A decision support system for antibiotic prescription based on local cumulative antibiograms. Journal of Biomedical Informatics. 84. 114–122. 15 indexed citations
13.
Juárez, José M., et al.. (2017). Monitoring elderly people at home with temporal Case-Based Reasoning. Knowledge-Based Systems. 134. 116–134. 23 indexed citations
14.
Massie, Stewart, et al.. (2015). Case-base maintenance with multi-objective evolutionary algorithms. Journal of Intelligent Information Systems. 46(2). 259–284. 5 indexed citations
15.
Juárez, José M., et al.. (2011). Case Selection Evaluation Methodology.. 17–29. 1 indexed citations
16.
Juárez, José M., et al.. (2008). Temporal similarity by measuring possibilistic uncertainty in CBR. Fuzzy Sets and Systems. 160(2). 214–230. 17 indexed citations
17.
Juárez, José M., et al.. (2007). Case representation ontology for case retrieval systems in medical domains. 168–173. 6 indexed citations
18.
Combi, Carlo, et al.. (2007). Conceptual Modeling of Temporal Clinical Workflows. Virtual Community of Pathological Anatomy (University of Castilla La Mancha). 70–81. 20 indexed citations
19.
Palma, José, José M. Juárez, Manuel Campos, & R. Marı́n. (2006). Fuzzy theory approach for temporal model-based diagnosis: An application to medical domains. Artificial Intelligence in Medicine. 38(2). 197–218. 28 indexed citations
20.
Palma, José, José M. Juárez, Manuel Campos, & R. Marı́n. (2004). A fuzzy approach to temporal model-based diagnosis for Intensive Care Units. European Conference on Artificial Intelligence. 868–872. 4 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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