Ursula Neumann

1.2k total citations
24 papers, 711 citations indexed

About

Ursula Neumann is a scholar working on Endocrine and Autonomic Systems, Epidemiology and Surgery. According to data from OpenAlex, Ursula Neumann has authored 24 papers receiving a total of 711 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Endocrine and Autonomic Systems, 7 papers in Epidemiology and 4 papers in Surgery. Recurrent topics in Ursula Neumann's work include Regulation of Appetite and Obesity (8 papers), Liver Disease Diagnosis and Treatment (4 papers) and Biochemical Analysis and Sensing Techniques (4 papers). Ursula Neumann is often cited by papers focused on Regulation of Appetite and Obesity (8 papers), Liver Disease Diagnosis and Treatment (4 papers) and Biochemical Analysis and Sensing Techniques (4 papers). Ursula Neumann collaborates with scholars based in Germany, Canada and United States. Ursula Neumann's co-authors include Timothy J. Kieffer, Dominik Heider, Anna M. D'souza, Maria M. Glavas, Scott D. Covey, Diego M. López, Frank K. Huynh, Ali Canbay, Julia Kälsch and Jan‐Peter Sowa and has published in prestigious journals such as PLoS ONE, Hepatology and Diabetes.

In The Last Decade

Ursula Neumann

22 papers receiving 698 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ursula Neumann Germany 16 214 184 174 164 112 24 711
Bulbul Ahmed United States 12 207 1.0× 381 2.1× 78 0.4× 217 1.3× 178 1.6× 36 959
Rui Wu China 18 116 0.5× 125 0.7× 21 0.1× 312 1.9× 80 0.7× 75 1.0k
John Bartels United States 14 297 1.4× 53 0.3× 39 0.2× 374 2.3× 48 0.4× 16 952
Ning Dong China 23 361 1.7× 74 0.4× 28 0.2× 360 2.2× 43 0.4× 70 1.3k
Adela Sitar-Tăut Romania 13 87 0.4× 74 0.4× 26 0.1× 82 0.5× 68 0.6× 60 552
Yi‐Ting Chen Taiwan 11 87 0.4× 106 0.6× 39 0.2× 96 0.6× 18 0.2× 19 642
Chih-Min Su Taiwan 17 315 1.5× 137 0.7× 12 0.1× 201 1.2× 72 0.6× 60 1.0k
Piotr Kalinowski Poland 13 329 1.5× 204 1.1× 25 0.1× 61 0.4× 132 1.2× 35 772
Jakob S. Hansen Denmark 14 174 0.8× 383 2.1× 30 0.2× 438 2.7× 202 1.8× 27 993

Countries citing papers authored by Ursula Neumann

Since Specialization
Citations

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

Fields of papers citing papers by Ursula Neumann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ursula Neumann

This figure shows the co-authorship network connecting the top 25 collaborators of Ursula Neumann. A scholar is included among the top collaborators of Ursula Neumann 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 Ursula Neumann. Ursula Neumann 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
1.
Beck, Niels C., et al.. (2024). Introducing ProsperNN—a Python package for forecasting with neural networks. PeerJ Computer Science. 10. e2481–e2481. 1 indexed citations
2.
Neumann, Ursula, et al.. (2021). Evaluating the impact of multivariate imputation by MICE in feature selection. PLoS ONE. 16(7). e0254720–e0254720. 58 indexed citations
3.
López, Diego M., et al.. (2021). Framework for the Ensemble of Feature Selection Methods. Applied Sciences. 11(17). 8122–8122. 31 indexed citations
4.
Schotten, Clemens, Lars P. Bechmann, Paul Manka, et al.. (2019). NAFLD-Associated Comorbidities in Advanced Stage HCC Do Not Alter the Safety and Efficacy of Yttrium-90 Radioembolization. Liver Cancer. 8(6). 491–504. 17 indexed citations
5.
Canbay, Ali, Julia Kälsch, Ursula Neumann, et al.. (2019). Non-invasive assessment of NAFLD as systemic disease—A machine learning perspective. PLoS ONE. 14(3). e0214436–e0214436. 51 indexed citations
6.
Baars, Theodor, Jan‐Peter Sowa, Ursula Neumann, et al.. (2018). Liver parameters as part of a non-invasive model for prediction of all-cause mortality after myocardial infarction. Archives of Medical Science. 16(1). 71–80. 10 indexed citations
7.
Armano, Giuliano, et al.. (2018). Phi-Delta-Diagrams: Software Implementation of a Visual Tool for Assessing Classifier and Feature Performance. Machine Learning and Knowledge Extraction. 1(1). 121–137. 2 indexed citations
8.
Neumann, Ursula, et al.. (2017). Lipid nanoparticle delivery of glucagon receptor siRNA improves glucose homeostasis in mouse models of diabetes. Molecular Metabolism. 6(10). 1161–1172. 26 indexed citations
9.
Neumann, Ursula, et al.. (2017). EFS: an ensemble feature selection tool implemented as R-package and web-application. BioData Mining. 10(1). 21–21. 68 indexed citations
10.
D'souza, Anna M., Ursula Neumann, Maria M. Glavas, & Timothy J. Kieffer. (2017). The glucoregulatory actions of leptin. Molecular Metabolism. 6(9). 1052–1065. 146 indexed citations
11.
Neumann, Ursula, et al.. (2016). Glucagon receptor gene deletion in insulin knockout mice modestly reduces blood glucose and ketones but does not promote survival. Molecular Metabolism. 5(8). 731–736. 24 indexed citations
12.
Riemenschneider, Mona, Robin Senge, Ursula Neumann, Eyke Hüllermeier, & Dominik Heider. (2016). Exploiting HIV-1 protease and reverse transcriptase cross-resistance information for improved drug resistance prediction by means of multi-label classification. BioData Mining. 9(1). 10–10. 24 indexed citations
13.
Baars, Theodor, Ursula Neumann, Jan‐Peter Sowa, et al.. (2016). In Acute Myocardial Infarction Liver Parameters Are Associated With Stenosis Diameter. Medicine. 95(6). e2807–e2807. 19 indexed citations
14.
Neumann, Ursula, Mona Riemenschneider, Jan‐Peter Sowa, et al.. (2016). Compensation of feature selection biases accompanied with improved predictive performance for binary classification by using a novel ensemble feature selection approach. BioData Mining. 9(1). 36–36. 41 indexed citations
15.
Denroche, Heather C., Ursula Neumann, Jerzy E. Kulpa, et al.. (2015). Leptin induces fasting hypoglycaemia in a mouse model of diabetes through the depletion of glycerol. Diabetologia. 58(5). 1100–1108. 22 indexed citations
16.
Neumann, Ursula, Sam Chen, Yuen Yi C. Tam, et al.. (2014). IGFBP2 Is Neither Sufficient nor Necessary for the Physiological Actions of Leptin on Glucose Homeostasis in Male ob/ob Mice. Endocrinology. 155(3). 716–725. 19 indexed citations
17.
Neumann, Ursula. (2012). Zusammenarbeit mit Eltern in interkultureller Perspektive. DDS – Die Deutsche Schule. 1 indexed citations
18.
Huynh, Frank K., Ursula Neumann, Ying Wang, et al.. (2012). A Role for Hepatic Leptin Signaling in Lipid Metabolism via Altered Very Low Density Lipoprotein Composition and Liver Lipase Activity in Mice. Hepatology. 57(2). 543–554. 64 indexed citations
19.
20.
Gogolin, Ingrid, Ursula Neumann, & Lutz R. Reuter. (2001). Schulbildung für Kinder aus Minderheiten in Deutschland 1989-1999. 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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