Ana M. Wägner

3.4k total citations
121 papers, 1.8k citations indexed

About

Ana M. Wägner is a scholar working on Endocrinology, Diabetes and Metabolism, Surgery and Genetics. According to data from OpenAlex, Ana M. Wägner has authored 121 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 73 papers in Endocrinology, Diabetes and Metabolism, 45 papers in Surgery and 28 papers in Genetics. Recurrent topics in Ana M. Wägner's work include Diabetes Management and Research (36 papers), Diabetes and associated disorders (26 papers) and Diabetes, Cardiovascular Risks, and Lipoproteins (26 papers). Ana M. Wägner is often cited by papers focused on Diabetes Management and Research (36 papers), Diabetes and associated disorders (26 papers) and Diabetes, Cardiovascular Risks, and Lipoproteins (26 papers). Ana M. Wägner collaborates with scholars based in Spain, Norway and Italy. Ana M. Wägner's co-authors include Jordi Ordóñez‐Llanos, Mercedes Rigla, Yeray Brito‐Casillas, Antonio Pérez, Susan M. Webb, Mauro Boronat, Frederic Bartumeus, José Luís Sánchez-Quesada, Carlos Melián and María José Barahona and has published in prestigious journals such as The Lancet, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

Ana M. Wägner

115 papers receiving 1.8k 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 M. Wägner Spain 24 979 618 264 220 213 121 1.8k
Bong‐Yun Cha South Korea 24 801 0.8× 364 0.6× 136 0.5× 222 1.0× 232 1.1× 51 1.7k
Maria Shubina United States 20 557 0.6× 687 1.1× 160 0.6× 116 0.5× 280 1.3× 43 1.8k
Manuel Aguilar‐Diosdado Spain 25 856 0.9× 391 0.6× 371 1.4× 289 1.3× 149 0.7× 152 2.0k
Carlos Antônio Negrato Brazil 24 858 0.9× 353 0.6× 338 1.3× 209 0.9× 190 0.9× 81 2.1k
Sihui Luo China 18 584 0.6× 393 0.6× 218 0.8× 209 0.9× 259 1.2× 78 2.2k
Rosa Corcoy Spain 33 1.2k 1.3× 1.5k 2.4× 333 1.3× 250 1.1× 173 0.8× 142 3.8k
Rüdiger Landgraf Germany 20 1.3k 1.3× 454 0.7× 314 1.2× 248 1.1× 123 0.6× 101 2.2k
Pedro Valdivielso Spain 25 563 0.6× 856 1.4× 254 1.0× 324 1.5× 642 3.0× 143 2.0k
Claudia Großmann Germany 29 1.2k 1.2× 475 0.8× 285 1.1× 165 0.8× 305 1.4× 68 2.3k
Connie B. Newman United States 26 1.5k 1.5× 1.2k 2.0× 189 0.7× 480 2.2× 278 1.3× 55 2.9k

Countries citing papers authored by Ana M. Wägner

Since Specialization
Citations

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

Fields of papers citing papers by Ana M. Wägner

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ana M. Wägner

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

All Works

20 of 20 papers shown
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Wägner, Ana M., et al.. (2025). Transfer learning for a tabular-to-image approach: A case study for cardiovascular disease prediction. Journal of Biomedical Informatics. 165. 104821–104821. 3 indexed citations
3.
Brito‐Casillas, Yeray, et al.. (2025). Mechanisms of Fetal Overgrowth in Gestational Diabetes: The Potential Role of SOCS2. Nutrients. 17(9). 1519–1519.
4.
Wägner, Ana M., et al.. (2025). Personalized glucose forecasting for people with type 1 diabetes using large language models. Computer Methods and Programs in Biomedicine. 265. 108737–108737. 3 indexed citations
5.
López‐Alcalde, Jesús, L. Susan Wieland, Jürgen Barth, et al.. (2024). Methodological challenges in systematic reviews of mHealth interventions: Survey and consensus-based recommendations. International Journal of Medical Informatics. 184. 105345–105345. 2 indexed citations
6.
Sánchez-Hernández, Rosa M., Núria Plana, Daiana Ibarretxe, et al.. (2024). Impact of PCSK9 inhibitors in glycaemic control and new-onset diabetes. Cardiovascular Diabetology. 23(1). 4–4. 6 indexed citations
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Perea, Verónica, Carmen Quirós, Ana M. Wägner, et al.. (2024). Pregnancy outcomes with the pregestational use of Minimed 780G compared to Minimed 640G: findings from a multicenter cohort study. Acta Diabetologica. 62(7). 1117–1128. 1 indexed citations
9.
Boronat, Mauro, et al.. (2023). Short‐term evaluation of renal markers in overweight adult cats. Veterinary Medicine and Science. 9(2). 572–578. 3 indexed citations
10.
Suárez, Nicolás M., Asier Benito‐Vicente, Yeray Brito‐Casillas, et al.. (2023). Age, Origin and Functional Study of the Prevalent LDLR Mutation Causing Familial Hypercholesterolaemia in Gran Canaria. International Journal of Molecular Sciences. 24(14). 11319–11319. 1 indexed citations
11.
Brito‐Casillas, Yeray, et al.. (2022). Ex vivo evaluation of adhesive strength and barrier effect of a novel treatment for esophagitis. Gastroenterología y Hepatología. 46(6). 455–461. 1 indexed citations
12.
Fabelo, Himar, Samuel Ortega, Eduardo Quevedo, et al.. (2022). Synthetic Patient Data Generation and Evaluation in Disease Prediction Using Small and Imbalanced Datasets. IEEE Journal of Biomedical and Health Informatics. 27(6). 2670–2680. 28 indexed citations
13.
Sánchez-Hernández, Rosa M., et al.. (2022). Diabetes and Familial Hypercholesterolemia: Interplay between Lipid and Glucose Metabolism. Nutrients. 14(7). 1503–1503. 17 indexed citations
14.
García‐Pérez, Lidia, Yolanda Ramallo‐Fariña, Laura Vallejo‐Torres, et al.. (2022). Cost-effectiveness of multicomponent interventions in type 2 diabetes mellitus in a cluster randomised controlled trial: the INDICA study. BMJ Open. 12(4). e058049–e058049. 2 indexed citations
15.
Álvarez‐Pérez, Yolanda, Lilisbeth Perestelo‐Pérez, Amado Rivero‐Santana, et al.. (2021). Cocreation of Massive Open Online Courses to Improve Digital Health Literacy in Diabetes: Pilot Mixed Methods Study. JMIR Diabetes. 6(4). e30603–e30603. 14 indexed citations
16.
Medina, Yeray Nóvoa, et al.. (2020). Epidemiology of childhood-onset type 1 diabetes in Gran Canaria (2006–2018). Endocrinología Diabetes y Nutrición (English ed ). 67(10). 658–664.
17.
Perestelo‐Pérez, Lilisbeth, Carina Soledad González González, Yolanda Álvarez‐Pérez, et al.. (2020). IC-Health Project: Development of MOOCs to Promote Digital Health Literacy: First Results and Future Challenges. Sustainability. 12(16). 6642–6642. 28 indexed citations
18.
Ramallo‐Fariña, Yolanda, Miguel Ángel García Bello, Lidia García‐Pérez, et al.. (2020). Effectiveness of Internet-Based Multicomponent Interventions for Patients and Health Care Professionals to Improve Clinical Outcomes in Type 2 Diabetes Evaluated Through the INDICA Study: Multiarm Cluster Randomized Controlled Trial. JMIR mhealth and uhealth. 8(11). e18922–e18922. 25 indexed citations
19.
Sánchez-Hernández, Rosa M., Maria Donata Di Taranto, Asier Benito‐Vicente, et al.. (2019). The Arg499His gain-of-function mutation in the C-terminal domain of PCSK9. Atherosclerosis. 289. 162–172. 19 indexed citations
20.

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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