S. Paredes

556 total citations
48 papers, 314 citations indexed

About

S. Paredes is a scholar working on Cardiology and Cardiovascular Medicine, Artificial Intelligence and Health Information Management. According to data from OpenAlex, S. Paredes has authored 48 papers receiving a total of 314 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Cardiology and Cardiovascular Medicine, 23 papers in Artificial Intelligence and 14 papers in Health Information Management. Recurrent topics in S. Paredes's work include ECG Monitoring and Analysis (16 papers), Machine Learning in Healthcare (14 papers) and Artificial Intelligence in Healthcare (14 papers). S. Paredes is often cited by papers focused on ECG Monitoring and Analysis (16 papers), Machine Learning in Healthcare (14 papers) and Artificial Intelligence in Healthcare (14 papers). S. Paredes collaborates with scholars based in Portugal, Germany and Finland. S. Paredes's co-authors include Teresa Rocha, J. Henriques, P. Carvalho, João Morais, M. Antunes, Matthew Harris, A.E. Ruano, M.G. Ruano, Diana Mendes and J. Habetha and has published in prestigious journals such as SHILAP Revista de lepidopterología, Computer Methods and Programs in Biomedicine and Computers in Biology and Medicine.

In The Last Decade

S. Paredes

44 papers receiving 300 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
S. Paredes Portugal	10	132	113	77	49	33	48	314
Teresa Rocha Portugal	11	136 1.0×	113 1.0×	75 1.0×	50 1.0×	35 1.1×	52	348
Sakyajit Bhattacharya India	11	72 0.5×	108 1.0×	40 0.5×	38 0.8×	30 0.9×	25	286
Takuma Shibahara Japan	8	82 0.6×	100 0.9×	80 1.0×	18 0.4×	9 0.3×	15	357
Deepta Rajan United States	8	42 0.3×	213 1.9×	64 0.8×	96 2.0×	7 0.2×	19	400
Dean A. Bodenham Switzerland	8	46 0.3×	174 1.5×	25 0.3×	34 0.7×	45 1.4×	10	379
Tae Joon Jun South Korea	11	103 0.8×	86 0.8×	33 0.4×	8 0.2×	48 1.5×	46	397
Johann-Jakob Schmid United States	7	129 1.0×	304 2.7×	194 2.5×	15 0.3×	22 0.7×	14	540
Alexandros C. Dimopoulos Greece	10	107 0.8×	44 0.4×	51 0.7×	4 0.1×	27 0.8×	25	343
Karl Øyvind Mikalsen Norway	11	16 0.1×	285 2.5×	39 0.5×	99 2.0×	11 0.3×	21	441
Eleni I. Georga Greece	13	108 0.8×	129 1.1×	198 2.6×	25 0.5×	102 3.1×	49	660

Countries citing papers authored by S. Paredes

Since Specialization

Citations

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

Fields of papers citing papers by S. Paredes

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of S. Paredes

This figure shows the co-authorship network connecting the top 25 collaborators of S. Paredes. A scholar is included among the top collaborators of S. Paredes 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 S. Paredes. S. Paredes 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

Sousa, Sérgio F., et al.. (2024). Machine learning models’ assessment: trust and performance. Medical & Biological Engineering & Computing. 62(11). 3397–3410. 2 indexed citations

Henriques, J., et al.. (2023). An interpretable machine learning approach to estimate the influence of inflammation biomarkers on cardiovascular risk assessment. Computer Methods and Programs in Biomedicine. 230. 107347–107347. 18 indexed citations

Henriques, J., et al.. (2021). A new approach for interpretability and reliability in clinical risk prediction: Acute coronary syndrome scenario. Artificial Intelligence in Medicine. 117. 102113–102113. 21 indexed citations

Rocha, Teresa, et al.. (2019). A Matlab Tool for Solving Linear Goal Programming Problems. 337–342. 6 indexed citations

Paredes, S., J. Henriques, Teresa Rocha, et al.. (2018). A Clinical Interpretable Approach Applied to Cardiovascular Risk Assessment. PubMed. 2018. 3252–3255. 2 indexed citations

Rocha, Teresa, S. Paredes, Ramona Cabiddu, et al.. (2016). A Tool For ECG Analysis as a Module of a Tele-Monitoring System. International Journal of Online and Biomedical Engineering (iJOE). 12(4). 64–67. 3 indexed citations

Paredes, S., Teresa Rocha, Diana Mendes, et al.. (2015). New approaches for improving cardiovascular risk assessment. Revista Portuguesa de Cardiologia. 35(1). 5–13. 5 indexed citations

Paredes, S., Teresa Rocha, P. Carvalho, et al.. (2015). Integration of Different Risk Assessment Tools to Improve Stratification of Patients with Coronary Artery Disease. Medical & Biological Engineering & Computing. 53(10). 1069–1083. 6 indexed citations

Henriques, J., et al.. (2015). Personalization Based on Grouping Strategies for Short-Term Cardiovascular Event Risk Assessment. Cardiovascular Engineering and Technology. 6(3). 392–399. 1 indexed citations

10.

Paredes, S., Teresa Rocha, P. Carvalho, et al.. (2015). The CardioRisk project: Improvement of cardiovascular risk assessment. Journal of Computational Science. 9. 39–44. 5 indexed citations

11.

Paredes, S., Teresa Rocha, P. Carvalho, et al.. (2012). Cardiovascular event risk assessment — Fusion of individual risk assessment tools applied to the Portuguese population. International Conference on Information Fusion. 925–932. 1 indexed citations

12.

Eilebrecht, Benjamin, J. Henriques, Teresa Rocha, et al.. (2012). Automatic Parameter Extraction from Capacitive ECG Measurements. Cardiovascular Engineering and Technology. 3(3). 319–332. 4 indexed citations

13.

Rocha, Teresa, S. Paredes, P. Carvalho, & J. Henriques. (2011). Prediction of acute hypotensive episodes by means of neural network multi-models. Computers in Biology and Medicine. 41(10). 881–890. 34 indexed citations

14.

Paredes, S., Teresa Rocha, P. Carvalho, et al.. (2011). Long term cardiovascular risk models’ combination. Computer Methods and Programs in Biomedicine. 101(3). 231–242. 19 indexed citations

15.

Rocha, Teresa, S. Paredes, P. Carvalho, & J. Henriques. (2011). A wavelet-based approach for time series pattern detection and events prediction applied to telemonitoring data. PubMed. 22. 6037–6040. 2 indexed citations

16.

Paredes, S., Teresa Rocha, P. Carvalho, et al.. (2011). Fusion of risk assessment models with application to coronary artery disease patients. PubMed. 26. 872–875. 3 indexed citations

17.

Paredes, S., Teresa Rocha, P. Carvalho, et al.. (2010). Cardiovascular risk and status assessment. PubMed. 2008. 2872–2876. 3 indexed citations

18.

Rocha, Teresa, S. Paredes, P. Carvalho, J. Henriques, & Matthew Harris. (2010). Wavelet based time series forecast with application to acute hypotensive episodes prediction. PubMed. 16. 2403–2406. 16 indexed citations

19.

Paredes, S., Teresa Rocha, P. Carvalho, et al.. (2009). Long term cardiovascular risk models’ combination - a new approach. PubMed. 2009. 4711–4714. 3 indexed citations

20.

Rocha, Teresa, S. Paredes, P. Carvalho, et al.. (2009). Ischemia detection in the context of a cardiovascular status assessment tool. PubMed. 2009. 2535–2538. 2 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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