Ana Subtil

436 total citations
11 papers, 291 citations indexed

About

Ana Subtil is a scholar working on Artificial Intelligence, Surgery and Public Health, Environmental and Occupational Health. According to data from OpenAlex, Ana Subtil has authored 11 papers receiving a total of 291 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Artificial Intelligence, 3 papers in Surgery and 3 papers in Public Health, Environmental and Occupational Health. Recurrent topics in Ana Subtil's work include Statistical Methods and Bayesian Inference (3 papers), Streptococcal Infections and Treatments (2 papers) and Advanced Statistical Methods and Models (2 papers). Ana Subtil is often cited by papers focused on Statistical Methods and Bayesian Inference (3 papers), Streptococcal Infections and Treatments (2 papers) and Advanced Statistical Methods and Models (2 papers). Ana Subtil collaborates with scholars based in Portugal, Taiwan and Paraguay. Ana Subtil's co-authors include M. Rosário Oliveira, Luzia Gonçalves, Nuno Sousa Pereira, Luís Carlos Matos, Teresa Amaral, P. de Zea Bermudez, Men‐Fang Shaio, Virgı́lio do Rosário, Catarina Gouveia and Pedro Aguiar and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.

In The Last Decade

Ana Subtil

11 papers receiving 280 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ana Subtil Portugal 6 142 93 49 44 36 11 291
Zuriati Ibrahim Malaysia 13 169 1.2× 60 0.6× 63 1.3× 69 1.6× 42 1.2× 48 551
Sadaf Kazi United States 9 38 0.3× 15 0.2× 22 0.4× 23 0.5× 19 0.5× 31 278
Honoria Ocagli Italy 9 38 0.3× 10 0.1× 19 0.4× 28 0.6× 31 0.9× 37 260
Jaewoong Bae South Korea 8 61 0.4× 34 0.4× 7 0.1× 30 0.7× 11 0.3× 15 281
Cynthia A. Launer United States 8 52 0.4× 92 1.0× 3 0.1× 14 0.3× 48 1.3× 9 497
Xiaoqing Xue Canada 12 43 0.3× 19 0.2× 42 0.9× 49 1.1× 30 0.8× 29 410
F Riccardi Italy 12 13 0.1× 29 0.3× 19 0.4× 56 1.3× 20 0.6× 35 323
Riyadh A. Alzaheb Saudi Arabia 13 26 0.2× 167 1.8× 2 0.0× 20 0.5× 76 2.1× 21 606
Rubens Antunes da Cruz Filho Brazil 10 109 0.8× 15 0.2× 9 0.2× 23 0.5× 34 0.9× 28 297
Carol Hill United States 9 24 0.2× 7 0.1× 8 0.2× 16 0.4× 12 0.3× 22 257

Countries citing papers authored by Ana Subtil

Since Specialization
Citations

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

Fields of papers citing papers by Ana Subtil

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ana Subtil

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

All Works

11 of 11 papers shown
1.
Subtil, Ana, M. Rosário Oliveira, Rui Valadas, Paulo Salvador, & António Pacheco. (2023). Detection of Internet‐wide traffic redirection attacks using machine learning techniques. IET Networks. 12(4). 179–195. 1 indexed citations
3.
Gouveia, Catarina, et al.. (2023). Osteoarticular Infections: Younger Children With Septic Arthritis and Low Inflammatory Patterns Have a Better Prognosis in a European Cohort. The Pediatric Infectious Disease Journal. 42(11). 969–974. 4 indexed citations
5.
Gonçalves, Luzia, Ana Subtil, M. Rosário Oliveira, & P. de Zea Bermudez. (2022). ROC Curve Estimation. SHILAP Revista de lepidopterología. 5 indexed citations
6.
Gouveia, Catarina, et al.. (2022). Distinguishing Kingella kingae from Pyogenic Acute Septic Arthritis in Young Portuguese Children. Microorganisms. 10(6). 1233–1233. 4 indexed citations
7.
Oliveira, M. Rosário, Ana Subtil, & Luzia Gonçalves. (2020). Common Medical and Statistical Problems: The Dilemma of the Sample Size Calculation for Sensitivity and Specificity Estimation. Mathematics. 8(8). 1258–1258. 1 indexed citations
8.
Gonçalves, Luzia, Ana Subtil, M. Rosário Oliveira, & P. de Zea Bermudez. (2014). ROC curve estimation: An overview. 12(1). 1–20. 66 indexed citations
9.
Gonçalves, Luzia, et al.. (2012). Bayesian Latent Class Models in Malaria Diagnosis. PLoS ONE. 7(7). e40633–e40633. 40 indexed citations
10.
Subtil, Ana, M. Rosário Oliveira, & Luzia Gonçalves. (2012). Conditional dependence diagnostic in the latent class model: A simulation study. Statistics & Probability Letters. 82(7). 1407–1412. 9 indexed citations
11.
Amaral, Teresa, et al.. (2007). The economic impact of disease-related malnutrition at hospital admission. Clinical Nutrition. 26(6). 778–784. 152 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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