Fernando Rua

527 total citations
38 papers, 190 citations indexed

About

Fernando Rua is a scholar working on Surgery, Artificial Intelligence and Health Information Management. According to data from OpenAlex, Fernando Rua has authored 38 papers receiving a total of 190 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Surgery, 12 papers in Artificial Intelligence and 11 papers in Health Information Management. Recurrent topics in Fernando Rua's work include Healthcare Technology and Patient Monitoring (16 papers), Artificial Intelligence in Healthcare (8 papers) and Big Data and Business Intelligence (5 papers). Fernando Rua is often cited by papers focused on Healthcare Technology and Patient Monitoring (16 papers), Artificial Intelligence in Healthcare (8 papers) and Big Data and Business Intelligence (5 papers). Fernando Rua collaborates with scholars based in Portugal, United States and Mexico. Fernando Rua's co-authors include Manuel Filipe Santos, Filipe Portela, Álvaro Silva, António Abelha, José Machado, José Neves, Bruno V. M. Rodrigues, André Gonçalves, Ana Pereira and Ana Ribeiro and has published in prestigious journals such as Information, Indian Journal of Science and Technology and Jurnal Teknologi.

In The Last Decade

Fernando Rua

36 papers receiving 177 citations

Peers

Fernando Rua

HIM

SURGE

EPIDE

Yaron Denekamp Israel

Ståle Walderhaug Norway

Blagoj Ristevski North Macedonia

Mustafa Yüksel Türkiye

Eliot Kimber United Kingdom

Erez Shalom Israel

Mohammad Adibuzzaman United States

Sophie Anne Inès Klopfenstein Germany

Magí Lluch-Ariet Spain

N. Maglaveras Greece

Yaron Denekamp Israel

Fernando Rua

91 ×1.3

HIM

78 ×1.2

38 ×0.8

SURGE

40 ×1.3

18 ×0.8

EPIDE

Citations per year, relative to Fernando Rua Fernando Rua (= 1×) peers Yaron Denekamp

Countries citing papers authored by Fernando Rua

Since Specialization

Citations

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

Fields of papers citing papers by Fernando Rua

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fernando Rua

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

Rua, Fernando, et al.. (2024). Application of the Simple Additive Weighting (SAW) Method in the Decision Support System for the Selection of Study Programs at the University of Papua. Jurnal Teknologi Terapan G-Tech. 8(4). 2420–2430. 1 indexed citations

Pereira, Ana, Filipe Portela, Manuel Filipe Santos, et al.. (2017). Pervasive Business Intelligence in Intensive Medicine - An Overview of a Clinical Solution. 37–41.

Portela, Filipe, et al.. (2017). Towards an Intelligent Systems to Predict Nosocomial Infections in Intensive Care. 150–155. 3 indexed citations

Portela, Filipe, Manuel Filipe Santos, José Machado, et al.. (2017). Categorize Readmitted Patients in Intensive Medicine by Means of Clustering Data Mining. International Journal of E-Health and Medical Communications. 8(3). 22–37. 5 indexed citations

Portela, Filipe, Manuel Filipe Santos, José Machado, António Abelha, & Fernando Rua. (2017). Step Towards Pervasive Technology Assessment in Intensive Medicine. RePEc: Research Papers in Economics. 6(2). 1–16. 1 indexed citations

Portela, Filipe, Manuel Filipe Santos, José Machado, et al.. (2016). Clustering data mining models to identify patterns in weaning patient failures. RepositóriUM (Universidade do Minho). 2 indexed citations

Portela, Filipe, Manuel Filipe Santos, António Abelha, et al.. (2015). Predict hourly patient discharge probability in Intensive Care Units using Data Mining. Indian Journal of Science and Technology. 8(32). 7 indexed citations

Pereira, Ana, Bruno V. M. Rodrigues, Filipe Portela, et al.. (2015). Improving Quality of Medical Service with Mobile Health Software. Procedia Computer Science. 63. 292–299. 13 indexed citations

Portela, Filipe, Manuel Filipe Santos, Álvaro Silva, et al.. (2014). Real-Time Predictive Analytics for Sepsis Level and Therapeutic Plans in Intensive Care Medicine. International Journal of Healthcare Information Systems and Informatics. 9(3). 36–54. 5 indexed citations

10.

Portela, Filipe, Manuel Filipe Santos, Álvaro Silva, et al.. (2013). Adoption of Pervasive Intelligent Information Systems in Intensive Medicine. Procedia Technology. 9. 1022–1032. 6 indexed citations

11.

Portela, Filipe, Manuel Filipe Santos, Álvaro Silva, et al.. (2013). Data Mining for Real-Time Intelligent Decision Support System in Intensive Care Medicine. 270–276. 3 indexed citations

12.

Portela, Filipe, Manuel Filipe Santos, José Machado, et al.. (2013). Real-Time Decision Support in Intensive Medicine: An intelligent approach for monitoring Data Quality. 2(1). 26–31. 5 indexed citations

13.

Portela, Filipe, Manuel Filipe Santos, José Machado, et al.. (2012). Intelligent decision support in Intensive Care : towards technology acceptance. RepositóriUM (Universidade do Minho). 3 indexed citations

14.

Portela, Filipe, Manuel Filipe Santos, Álvaro Silva, et al.. (2011). Enabling real-time intelligent decision support in intensive care. RepositóriUM (Universidade do Minho). 8 indexed citations

15.

Portela, Filipe, Manuel Filipe Santos, Álvaro Silva, et al.. (2011). KNOWLEDGE DISCOVERY FOR PERVASIVE AND REAL-TIME INTELLIGENT DECISION SUPPORT IN INTENSIVE CARE MEDICINE. RepositóriUM (Universidade do Minho). 241–249. 11 indexed citations

16.

Portela, Filipe, et al.. (2010). Distributed and real time data mining in the intensive care unit. European Conference on Artificial Intelligence. 4 indexed citations

17.

Portela, Filipe, et al.. (2010). Real-time prediction of organ failure and outcome in intensive medicine. Iberian Conference on Information Systems and Technologies. 1–6. 2 indexed citations

18.

Santos, Manuel Filipe, et al.. (2010). HOURLY PREDICTION OF ORGAN FAILURE AND OUTCOME IN INTENSIVE CARE BASED ON DATA MINING TECHNIQUES. 270–277. 4 indexed citations

19.

Santos, Manuel Filipe, Filipe Portela, José Machado, et al.. (2009). Nursing information architecture for situated decision support in intensive care units. RepositóriUM (Universidade do Minho). 18(3). 491–496. 2 indexed citations

20.

Santos, Manuel Filipe, Filipe Portela, José Machado, et al.. (2009). Information architecture for intelligent decision support in intensive medicine. RepositóriUM (Universidade do Minho). 8(5). 810–819. 8 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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