Frank Schwartz

2.5k total citations
82 papers, 1.8k citations indexed

About

Frank Schwartz is a scholar working on Endocrinology, Diabetes and Metabolism, Genetics and Epidemiology. According to data from OpenAlex, Frank Schwartz has authored 82 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Endocrinology, Diabetes and Metabolism, 14 papers in Genetics and 13 papers in Epidemiology. Recurrent topics in Frank Schwartz's work include Diabetes Management and Research (26 papers), Diabetes and associated disorders (12 papers) and Diabetes Management and Education (11 papers). Frank Schwartz is often cited by papers focused on Diabetes Management and Research (26 papers), Diabetes and associated disorders (12 papers) and Diabetes Management and Education (11 papers). Frank Schwartz collaborates with scholars based in United States, Germany and Iran. Frank Schwartz's co-authors include Jay H. Shubrook, Răzvan Bunescu, Cynthia R. Marling, Cindy Marling, Stefan Voß, Carsten Eggers, Todd Doyle, Mary de Groot, Kelly D. McCall and Godwin Dogbey and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Brain.

In The Last Decade

Frank Schwartz

80 papers receiving 1.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Frank Schwartz United States 26 814 254 241 220 206 82 1.8k
Jerry D. Cavallerano United States 32 507 0.6× 170 0.7× 135 0.6× 439 2.0× 153 0.7× 87 4.9k
Tyler Hyungtaek Rim South Korea 28 238 0.3× 156 0.6× 68 0.3× 381 1.7× 124 0.6× 134 4.1k
Yih Chung Tham Singapore 37 309 0.4× 210 0.8× 151 0.6× 1.2k 5.7× 187 0.9× 238 10.7k
Gavin Siew Wei Tan Singapore 37 366 0.4× 80 0.3× 111 0.5× 893 4.1× 138 0.7× 119 6.7k
Mercedes Rigla Spain 25 969 1.2× 28 0.1× 319 1.3× 190 0.9× 544 2.6× 82 2.0k
Paul Cooper United Kingdom 18 157 0.2× 291 1.1× 103 0.4× 285 1.3× 277 1.3× 46 2.2k
Dipika Bansal India 23 401 0.5× 396 1.6× 84 0.3× 392 1.8× 397 1.9× 106 2.4k
Alberto Maran Italy 26 1.8k 2.2× 69 0.3× 838 3.5× 233 1.1× 1.0k 4.9× 57 2.6k
Spyros Deftereos Greece 17 358 0.4× 54 0.2× 153 0.6× 465 2.1× 207 1.0× 51 2.0k
Yunlong Zhang China 32 397 0.5× 274 1.1× 168 0.7× 943 4.3× 382 1.9× 123 3.2k

Countries citing papers authored by Frank Schwartz

Since Specialization
Citations

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

Fields of papers citing papers by Frank Schwartz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Frank Schwartz

This figure shows the co-authorship network connecting the top 25 collaborators of Frank Schwartz. A scholar is included among the top collaborators of Frank Schwartz 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 Frank Schwartz. Frank Schwartz 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.
McCall, Kelly D., Jean Thuma, Marı́a C. Courrèges, et al.. (2023). Anti-Inflammatory and Therapeutic Effects of a Novel Small-Molecule Inhibitor of Inflammation in a Male C57BL/6J Mouse Model of Obesity-Induced NAFLD/MAFLD. Journal of Inflammation Research. Volume 16. 5339–5366. 3 indexed citations
2.
Pelzer, Esther A., Corina Melzer, Frank Schwartz, et al.. (2022). Clustering of Parkinson subtypes reveals strong influence of DRD2 polymorphism and gender. Scientific Reports. 12(1). 6038–6038. 6 indexed citations
3.
Benner, Sarah E., Jean Thuma, Ramiro Malgor, et al.. (2020). Coxsackievirus B4 Exposure Results in Variable Pattern Recognition Response in the Kidneys of Female Non-Obese Diabetic Mice Before Establishment of Diabetes. Viral Immunology. 33(7). 494–506. 5 indexed citations
4.
Schwartz, Frank, Masoud Tahmasian, Franziska Maier, et al.. (2018). Overlapping and distinct neural metabolic patterns related to impulsivity and hypomania in Parkinson’s disease. Brain Imaging and Behavior. 13(1). 241–254. 10 indexed citations
5.
Groot, Mary de, David G. Marrero, Lisa Mele, et al.. (2017). Depressive Symptoms, Antidepressant Medication Use, and Inflammatory Markers in the Diabetes Prevention Program. Psychosomatic Medicine. 80(2). 167–173. 9 indexed citations
6.
Tahmasian, Masoud, Simon B. Eickhoff, Kathrin Giehl, et al.. (2017). Resting-state functional reorganization in Parkinson's disease: An activation likelihood estimation meta-analysis. Cortex. 92. 119–138. 102 indexed citations
7.
O’Brien, John, Sudhir P. Deosarkar, Olivia L. Lanier, et al.. (2017). Phenylmethimazole and a thiazole derivative of phenylmethimazole inhibit IL-6 expression by triple negative breast cancer cells. European Journal of Pharmacology. 803. 130–137. 18 indexed citations
8.
Deosarkar, Sudhir P., Olivia L. Lanier, Monica M. Burdick, et al.. (2015). Simple modifications to methimazole that enhance its inhibitory effect on tumor necrosis factor-α-induced vascular cell adhesion molecule-1 expression by human endothelial cells. European Journal of Pharmacology. 751. 59–66. 8 indexed citations
9.
Bunescu, Răzvan, et al.. (2014). A Machine Learning Approach to Predicting Blood Glucose Levels for Diabetes Management. National Conference on Artificial Intelligence. 80 indexed citations
10.
Schwartz, Frank & Cynthia R. Marling. (2014). Glycemic Variability in Type 1 DiabetesDoes It Matter?. US Endocrinology. 10(1). 20–20. 3 indexed citations
11.
Doyle, Todd, Mary de Groot, Tamara B. Harris, et al.. (2013). Diabetes, depressive symptoms, and inflammation in older adults: Results from the Health, Aging, and Body Composition Study. Journal of Psychosomatic Research. 75(5). 419–424. 40 indexed citations
12.
Schwartz, Frank & Cynthia R. Marling. (2013). Use of Automated Bolus Calculators for Diabetes Management. US Endocrinology. 9(2). 124–124. 1 indexed citations
13.
14.
Marling, Cynthia R., et al.. (2011). Characterizing Blood Glucose Variability Using New Metrics with Continuous Glucose Monitoring Data. Journal of Diabetes Science and Technology. 5(4). 871–878. 56 indexed citations
15.
McCall, Kelly D., Dawn K. Holliday, Eric Dickerson, et al.. (2010). Phenylmethimazole blocks palmitate-mediated induction of inflammatory cytokine pathways in 3T3L1 adipocytes and RAW 264.7 macrophages. Journal of Endocrinology. 207(3). 343–353. 48 indexed citations
16.
Schwartz, Frank, et al.. (2009). High Self‐Reported Prevalence of Diabetes Mellitus, Heart Disease, and Stroke in 11 Counties of Rural Appalachian Ohio. The Journal of Rural Health. 25(2). 226–230. 31 indexed citations
17.
Shubrook, Jay H., et al.. (2009). Exploration of the DPP-4 inhibitors with a focus on saxagliptin. Expert Opinion on Pharmacotherapy. 10(17). 2927–2934. 4 indexed citations
18.
Schwartz, Frank, et al.. (2008). Evaluation of Diabetes Management In A Rural Community Hospital. Endocrine Practice. 14(1). 50–57. 2 indexed citations
19.
Hummel, Marybeth, et al.. (2007). Novel CDH3 mutations in hypotrichosis with juvenile macular dystrophy. Clinical and Experimental Dermatology. 32(2). 191–196. 26 indexed citations
20.
Schwartz, Frank & Stefan Voß. (2007). Distribution network design with postponement. Journal of the Association for Information Systems. 373–390. 5 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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