Deanna Cheek

722 total citations
8 papers, 578 citations indexed

About

Deanna Cheek is a scholar working on Nephrology, Cardiology and Cardiovascular Medicine and Endocrinology, Diabetes and Metabolism. According to data from OpenAlex, Deanna Cheek has authored 8 papers receiving a total of 578 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Nephrology, 2 papers in Cardiology and Cardiovascular Medicine and 2 papers in Endocrinology, Diabetes and Metabolism. Recurrent topics in Deanna Cheek's work include Dialysis and Renal Disease Management (3 papers), Renal Diseases and Glomerulopathies (2 papers) and Blood Pressure and Hypertension Studies (2 papers). Deanna Cheek is often cited by papers focused on Dialysis and Renal Disease Management (3 papers), Renal Diseases and Glomerulopathies (2 papers) and Blood Pressure and Hypertension Studies (2 papers). Deanna Cheek collaborates with scholars based in United States. Deanna Cheek's co-authors include David W. Ploth, Lawrence Y. Agodoa, John P. Middleton, Julia B. Lewis, Tom Greene, Daniel O’Connor, Mohammed Sika, Robert A. Phillips, Sally Self and Lawrence J. Appel and has published in prestigious journals such as Journal of the American Society of Nephrology, American Journal of Kidney Diseases and Nephrology Dialysis Transplantation.

In The Last Decade

Deanna Cheek

8 papers receiving 557 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Deanna Cheek United States	8	389	116	110	92	86	8	578
Josep Bonet Spain	16	303 0.8×	117 1.0×	121 1.1×	78 0.8×	178 2.1×	34	691
Taner Baştürk Türkiye	15	397 1.0×	59 0.5×	83 0.8×	105 1.1×	119 1.4×	75	717
Shoichi Fujimoto Japan	8	379 1.0×	78 0.7×	119 1.1×	116 1.3×	69 0.8×	13	625
Ki Heon Nam South Korea	18	380 1.0×	89 0.8×	90 0.8×	98 1.1×	85 1.0×	38	693
Abdülkadir Ünsal Türkiye	16	406 1.0×	47 0.4×	98 0.9×	103 1.1×	141 1.6×	63	741
Audrey B. Tuttle United States	9	369 0.9×	84 0.7×	98 0.9×	88 1.0×	62 0.7×	10	637
Shuji Ohba Japan	4	275 0.7×	95 0.8×	132 1.2×	48 0.5×	54 0.6×	13	497
François Chantrel France	13	250 0.6×	190 1.6×	73 0.7×	51 0.6×	122 1.4×	46	577
Beat Schwegler Switzerland	6	324 0.8×	127 1.1×	121 1.1×	79 0.9×	79 0.9×	10	580
Dae-Suk Han South Korea	16	540 1.4×	79 0.7×	42 0.4×	89 1.0×	194 2.3×	23	749

Countries citing papers authored by Deanna Cheek

Since Specialization

Citations

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

Fields of papers citing papers by Deanna Cheek

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Deanna Cheek

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

All Works

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8 of 8 papers shown

Lea, Janice P., Deanna Cheek, Lawrence J. Appel, et al.. (2008). Metabolic Syndrome, Proteinuria, and the Risk of Progressive CKD in Hypertensive African Americans. American Journal of Kidney Diseases. 51(5). 732–740. 64 indexed citations

Bhatnagar, Vibha, Daniel T. O’Connor, Nicholas J. Schork, et al.. (2007). Angiotensin-converting enzyme gene polymorphism predicts the time-course of blood pressure response to angiotensin converting enzyme inhibition in the AASK trial. Journal of Hypertension. 25(10). 2082–2092. 40 indexed citations

Wang, Wei, et al.. (2005). Glomerular filtration rate can be accurately predicted using lean mass measured by dual-energy X-ray absorptiometry. Nephrology Dialysis Transplantation. 21(1). 84–87. 28 indexed citations

Zhao, Wenle, et al.. (2005). PREVALENCE, TREATMENT, AND CONTROL OF HYPERTENSION AMONG AFRICAN AMERICANS AND CAUCASIANS AT PRIMARY CARE SITES FOR MEDICALLY UNDER-SERVED PATIENTS. PubMed. 15(1). 25–32. 19 indexed citations

Cheek, Deanna. (2005). Comprehensive Clinical Nephrology. Advances in Chronic Kidney Disease. 12(1). 113–113. 7 indexed citations

Cheek, Deanna, et al.. (2003). IgA antiglomerular basement membrane nephritis associated with crohn's disease: a case report and review of glomerulonephritis in inflammatory bowel disease. American Journal of Kidney Diseases. 41(5). 1097–1109. 49 indexed citations

Lewis, Julia B., Lawrence Y. Agodoa, Deanna Cheek, et al.. (2001). Comparison of cross-sectional renal function measurements in African Americans with hypertensive nephrosclerosis and of primary formulas to estimate glomerular filtration rate. American Journal of Kidney Diseases. 38(4). 744–753. 189 indexed citations

Cheek, Deanna, et al.. (1996). Calciphylaxis in chronic renal failure.. Journal of the American Society of Nephrology. 7(7). 978–982. 182 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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