José M. Juárez
- Artificial Intelligence top 5%
- Health Information Management top 2%
- Information Systems top 10%
- Molecular Biology
- Management Information Systems top 10%
- Co-authors
- Manuel CamposR. Marı́nJosé PalmaCarlo CombiFernando JiménezAntonio MoralesGracia SánchezBarbara Oliboni
- Topics
- Semantic Web and Ontologies (17 papers)AI-based Problem Solving and Planning (14 papers)Biomedical Text Mining and Ontologies (9 papers)
- Journals
- SHILAP Revista de lepidopterologíaScientific ReportsExpert Systems with Applications
- Partner nations
- SpainItalyUnited Kingdom
In The Last Decade
José M. Juárez
49 papers receiving 467 citations
Peers
Comparison fields: 5 of 107
- Artificial Intelligence 252
- Health Information Management 86
- Information Systems 78
- Molecular Biology 73
- Management Information Systems 62
Countries citing papers authored by José M. Juárez
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
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
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 0 | |
| 6 | 4 | |
| 7 | 2 | |
| 8 | 10 | |
| 9 | 2 | |
| 10 | 5 | |
| 11 | 2 | |
| 12 | 5 | |
| 13 | 13 | |
| 14 | Fenómenos emergentes relacionados con las amenazas híbridas y respuesta de la Unión Europea | 0 |
| 15 | 4 | |
| 16 | 16 | |
| 17 | Case Selection Evaluation Methodology. | 1 |
| 18 | Case representation ontology for case retrieval systems in medical domains | 6 |
| 19 | 28 | |
| 20 | A fuzzy approach to temporal model-based diagnosis for Intensive Care Units | 4 |
About José M. Juárez
José M. Juárez is a scholar working on Health Information Management, Applied Microbiology and Biotechnology and Artificial Intelligence, having authored 56 papers that have together received 481 indexed citations. Recurring topics across this work include Semantic Web and Ontologies (17 papers), AI-based Problem Solving and Planning (14 papers) and Biomedical Text Mining and Ontologies (9 papers). The work is most often cited by research in Health Information Management (86 citations), Applied Microbiology and Biotechnology (26 citations) and Health Informatics (13 citations). José M. Juárez has collaborated with scholars based in Spain, Italy and United Kingdom. Frequent co-authors include Manuel Campos, R. Marı́n, José Palma, Carlo Combi, Fernando Jiménez, Antonio Morales, Gracia Sánchez, Barbara Oliboni, Francisco Palácios and Huilong Duan. Their work appears in journals such as SHILAP Revista de lepidopterología, Scientific Reports and Expert Systems with Applications.
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.