Jaume Bacardit

7.6k total citations · 2 hit papers
106 papers, 3.5k citations indexed

About

Jaume Bacardit is a scholar working on Artificial Intelligence, Molecular Biology and Rheumatology. According to data from OpenAlex, Jaume Bacardit has authored 106 papers receiving a total of 3.5k indexed citations (citations by other indexed papers that have themselves been cited), including 46 papers in Artificial Intelligence, 32 papers in Molecular Biology and 19 papers in Rheumatology. Recurrent topics in Jaume Bacardit's work include Evolutionary Algorithms and Applications (38 papers), Metaheuristic Optimization Algorithms Research (27 papers) and Osteoarthritis Treatment and Mechanisms (19 papers). Jaume Bacardit is often cited by papers focused on Evolutionary Algorithms and Applications (38 papers), Metaheuristic Optimization Algorithms Research (27 papers) and Osteoarthritis Treatment and Mechanisms (19 papers). Jaume Bacardit collaborates with scholars based in United Kingdom, Spain and United States. Jaume Bacardit's co-authors include Natalio Krasnogor, Francisco Herrera, Salvador García, Josep M. Garrell, Luciano Sánchez, Jesús Alcalá‐Fdez, Juan Carlos Fernández Fernández, Sebastián Ventura, María José del Jesús and José Otero and has published in prestigious journals such as SHILAP Revista de lepidopterología, Bioinformatics and PLoS ONE.

In The Last Decade

Jaume Bacardit

102 papers receiving 3.4k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

KEEL: a software tool to assess evolutionary algorithms for data mining problems

2008 1.2k citations Jaume Bacardit et al. profile →
Osteoarthritis endotype discovery via clustering of biochemical marker data

2022 97 citations Paweł Widera, Ali Mobasheri et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jaume Bacardit United Kingdom	26	1.9k	720	508	328	313	106	3.5k
Chengye Li China	32	1.9k 1.0×	315 0.4×	639 1.3×	74 0.2×	28 0.1×	76	3.6k
Francisco Azuaje United Kingdom	33	1.0k 0.5×	2.5k 3.5×	491 1.0×	205 0.6×	31 0.1×	146	5.6k
Shinn‐Ying Ho Taiwan	40	645 0.3×	2.1k 2.9×	537 1.1×	68 0.2×	88 0.3×	163	4.6k
Thomas Jansen Germany	35	1.8k 1.0×	733 1.0×	1.1k 2.2×	67 0.2×	164 0.5×	148	4.3k
Haim Kaplan Israel	36	1.3k 0.7×	299 0.4×	1.2k 2.5×	340 1.0×	14 0.0×	253	4.6k
Mark Craven United States	37	3.3k 1.8×	1.3k 1.8×	312 0.6×	822 2.5×	12 0.0×	106	6.0k
Shimin Li China	19	1.6k 0.9×	234 0.3×	603 1.2×	115 0.4×	19 0.1×	91	3.5k
Abdul Sattar Australia	33	666 0.4×	1.9k 2.6×	664 1.3×	158 0.5×	11 0.0×	290	4.3k
Yves Chauvin United States	16	801 0.4×	1.5k 2.1×	304 0.6×	144 0.4×	15 0.0×	26	3.1k

Countries citing papers authored by Jaume Bacardit

Since Specialization

Citations

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

Fields of papers citing papers by Jaume Bacardit

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jaume Bacardit

This figure shows the co-authorship network connecting the top 25 collaborators of Jaume Bacardit. A scholar is included among the top collaborators of Jaume Bacardit 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 Jaume Bacardit. Jaume Bacardit is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Bacardit, Jaume, et al.. (2025). The MacqD deep-learning-based model for automatic detection of socially housed laboratory macaques. Scientific Reports. 15(1). 11883–11883. 1 indexed citations

Bacardit, Jaume, Maw Pin Tan, Nor Izzati Saedon, et al.. (2024). Artificial intelligence driven clustering of blood pressure profiles reveals frailty in orthostatic hypertension. Experimental Physiology. 110(2). 230–247. 1 indexed citations

Bacardit, Jaume, Alexander E. I. Brownlee, Stefano Cagnoni, et al.. (2024). Evolutionary Computation and Explainable AI: A Roadmap to Understandable Intelligent Systems. IEEE Transactions on Evolutionary Computation. 29(5). 2213–2228. 6 indexed citations

Schmidt, Lena, et al.. (2023). Automated data analysis of unstructured grey literature in health research: A mapping review. Research Synthesis Methods. 15(2). 178–197. 1 indexed citations

Wipat, Anil, et al.. (2023). Transcriptional biomarker discovery toward building a load stress reporting system for engineered Escherichia coli strains. Biotechnology and Bioengineering. 121(1). 355–365. 2 indexed citations

Elezgaray, Juan, et al.. (2023). Reverse engineering DNA origami nanostructure designs from raw scaffold and staple sequence lists. Computational and Structural Biotechnology Journal. 21. 3615–3626. 1 indexed citations

Jansen, Mylène P., W. Wirth, Jaume Bacardit, et al.. (2023). Machine-learning predicted and actual 2-year structural progression in the IMI-APPROACH cohort. Quantitative Imaging in Medicine and Surgery. 13(5). 3298–3306. 4 indexed citations

Iqbal, Sadaf, Jaume Bacardit, Bridget Griffiths, & John Allen. (2023). Deep learning classification of systemic sclerosis from multi-site photoplethysmography signals. Frontiers in Physiology. 14. 1242807–1242807. 2 indexed citations

Sinha, Nishant, et al.. (2022). A knowledge integration strategy for the selection of a robust multi-stress biomarkers panel for Bacillus subtilis. Synthetic and Systems Biotechnology. 8(1). 97–106.

10.

Jansen, Mylène P., W. Wirth, Frank W. Roemer, et al.. (2022). ASSOCIATIONS BETWEEN PREDICTED AND ACTUAL STRUCTURAL PROGRESSION IN THE APPROACH COHORT. Osteoarthritis and Cartilage. 30. S283–S284. 1 indexed citations

11.

Smith, Wendy D., et al.. (2021). Computational Strategies for the Identification of a Transcriptional Biomarker Panel to Sense Cellular Growth States in Bacillus subtilis. Sensors. 21(7). 2436–2436. 3 indexed citations

12.

Groß, Thomas, et al.. (2021). Is it feasible to detect FLOSS version release events from textual messages? A case study on Stack Overflow. PLoS ONE. 16(2). e0246464–e0246464. 3 indexed citations

13.

Alameer, Ali, I. Kyriazakis, & Jaume Bacardit. (2020). Automated recognition of postures and drinking behaviour for the detection of compromised health in pigs. Scientific Reports. 10(1). 13665–13665. 74 indexed citations

14.

Runhaar, J., Anne‐Christine Bay‐Jensen, Christian S. Thudium, et al.. (2017). A machine learning approach for the identification of new biomarkers for knee osteoarthritis development in overweight and obese women. Osteoarthritis and Cartilage. 25(12). 2014–2021. 62 indexed citations

15.

Bacardit, Jaume, et al.. (2017). RGIFE: a ranked guided iterative feature elimination heuristic for the identification of biomarkers. BMC Bioinformatics. 18(1). 322–322. 12 indexed citations

16.

Bacardit, Jaume, et al.. (2014). Hard Data Analytics Problems Make for Better Data Analysis Algorithms: Bioinformatics as an Example. Big Data. 2(3). 164–176. 6 indexed citations

17.

Swan, Anna, Ali Mobasheri, David Allaway, Susan Liddell, & Jaume Bacardit. (2013). Application of Machine Learning to Proteomics Data: Classification and Biomarker Identification in Postgenomics Biology. OMICS A Journal of Integrative Biology. 17(12). 595–610. 169 indexed citations

18.

Bacardit, Jaume, et al.. (2010). Learning Classifier Systems : 11th International Workshop, IWLCS 2008, Atlanta, GA, USA, July 13, 2008, and 12th International Workshop, IWLCS 2009, Montreal, QC, Canada, July 9, 2009 : revised selected papers. Springer eBooks. 1 indexed citations

19.

Bacardit, Jaume, Michael B. Stout, Jonathan D. Hirst, et al.. (2009). Automated Alphabet Reduction for Protein Datasets. BMC Bioinformatics. 10(1). 6–6. 46 indexed citations

20.

Bacardit, Jaume, Ester Bernadó-Mansilla, Martin V. Butz, et al.. (2008). Learning Classifier Systems: 10th International Workshop, IWLCS 2006, Seattle, MA, USA, July 8, 2006 and 11th International Workshop, IWLCS 2007, London, UK, July 8, 2007, Revised Selected Papers. Springer eBooks. 6 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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