Adam E. Gawęda

922 total citations
36 papers, 565 citations indexed

About

Adam E. Gawęda is a scholar working on Hematology, Nephrology and Genetics. According to data from OpenAlex, Adam E. Gawęda has authored 36 papers receiving a total of 565 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Hematology, 14 papers in Nephrology and 9 papers in Genetics. Recurrent topics in Adam E. Gawęda's work include Erythropoietin and Anemia Treatment (18 papers), Iron Metabolism and Disorders (8 papers) and Dialysis and Renal Disease Management (8 papers). Adam E. Gawęda is often cited by papers focused on Erythropoietin and Anemia Treatment (18 papers), Iron Metabolism and Disorders (8 papers) and Dialysis and Renal Disease Management (8 papers). Adam E. Gawęda collaborates with scholars based in United States, Poland and Australia. Adam E. Gawęda's co-authors include Michael E. Brier, George R. Aronoff, Alfred A. Jacobs, Jacek M. Żurada, Mehmet K. Muezzinoglu, L. Jane Goldsmith, Eleanor D. Lederer, N. Shesh, Jacek M. Zurada and Andrew T. Dailey and has published in prestigious journals such as Kidney International, Journal of the American Society of Nephrology and American Journal of Kidney Diseases.

In The Last Decade

Adam E. Gawęda

36 papers receiving 545 citations

Peers

Adam E. Gawęda
Alfred A. Jacobs United States
Flavio Mari Germany
Jakob Zierk Germany
Rajesh Shrivastava India
Roland Winkler Germany
Mathews B. Fish United States
Pankaj Mathur United States
Yihe Yang China
D. Wexler Israel
Irfan Khan United States
Alfred A. Jacobs United States
Adam E. Gawęda
Citations per year, relative to Adam E. Gawęda Adam E. Gawęda (= 1×) peers Alfred A. Jacobs

Countries citing papers authored by Adam E. Gawęda

Since Specialization
Citations

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

Fields of papers citing papers by Adam E. Gawęda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Adam E. Gawęda. 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 Adam E. Gawęda. The network helps show where Adam E. Gawęda may publish in the future.

Co-authorship network of co-authors of Adam E. Gawęda

This figure shows the co-authorship network connecting the top 25 collaborators of Adam E. Gawęda. A scholar is included among the top collaborators of Adam E. Gawęda 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 Adam E. Gawęda. Adam E. Gawęda 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.
Gawęda, Adam E., Michael E. Brier, & Eleanor D. Lederer. (2024). Leveraging quantitative systems pharmacology and artificial intelligence to advance treatment of chronic kidney disease mineral bone disorder. American Journal of Physiology-Renal Physiology. 327(3). F351–F362. 3 indexed citations
2.
Brier, Michael E. & Adam E. Gawęda. (2024). An Artificial Intelligence-Based Program Significantly Reduces ESA (Erythropoiesis-Stimulating Agent) Use and Maintains Hemoglobin. Journal of the American Society of Nephrology. 35(10S). 1 indexed citations
3.
Gawęda, Adam E., Eleanor D. Lederer, & Michael E. Brier. (2022). Use of Artificial Intelligence to Identify New Mechanisms and Approaches to Therapy of Bone Disorders Associated With Chronic Kidney Disease. Frontiers in Medicine. 9. 807994–807994. 6 indexed citations
4.
Gawęda, Adam E., Michael E. Brier, & Eleanor D. Lederer. (2021). Development of a Machine Learning Approach to Management of CKD-MBD Therapy. Journal of the American Society of Nephrology. 32(10S). 217–218. 1 indexed citations
5.
Merchant, Michael L., Jeffrey D. Ritzenthaler, Ming Li, et al.. (2020). Redox States of Protein Cysteines in Pathways of Protein Turnover and Cytoskeleton Dynamics Are Changed with Aging and Reversed by Slc7a11 Restoration in Mouse Lung Fibroblasts. Oxidative Medicine and Cellular Longevity. 2020. 1–17. 11 indexed citations
6.
Brier, Michael E., Adam E. Gawęda, & George R. Aronoff. (2018). Personalized Anemia Management and Precision Medicine in ESA and Iron Pharmacology in End-Stage Kidney Disease. Seminars in Nephrology. 38(4). 410–417. 17 indexed citations
7.
Mirinejad, Hossein, Adam E. Gawęda, Michael E. Brier, Jacek M. Żurada, & Tamer Inanc. (2017). Individualized drug dosing using RBF-Galerkin method: Case of anemia management in chronic kidney disease. Computer Methods and Programs in Biomedicine. 148. 45–53. 9 indexed citations
8.
Mirinejad, Hossein, Tamer Inanc, Michael E. Brier, & Adam E. Gawęda. (2015). RBF-based receding horizon control approach to personalized anemia treatment. 47. 1–2. 2 indexed citations
9.
Gawęda, Adam E., et al.. (2014). Impact of Patient Awareness on Access to Transplantation in End Stage Renal Disease. 3(2). 67–71. 1 indexed citations
10.
Gawęda, Adam E., George R. Aronoff, Alfred A. Jacobs, N. Shesh, & Michael E. Brier. (2013). Individualized Anemia Management Reduces Hemoglobin Variability in Hemodialysis Patients. Journal of the American Society of Nephrology. 25(1). 159–166. 42 indexed citations
11.
Krzyżański, Wojciech, et al.. (2013). Reticulocyte-based estimation of red blood cell lifespan. Experimental Hematology. 41(9). 817–822. 9 indexed citations
12.
Brier, Michael E. & Adam E. Gawęda. (2011). Predictive modeling for improved anemia management in dialysis patients. Current Opinion in Nephrology & Hypertension. 20(6). 573–576. 9 indexed citations
13.
Merchant, Michael L., Adam E. Gawęda, Daniel W. Wilkey, et al.. (2010). Oncostatin M receptor β and cysteine/histidine-rich 1 are biomarkers of the response to erythropoietin in hemodialysis patients. Kidney International. 79(5). 546–554. 6 indexed citations
14.
Gawęda, Adam E., L. Jane Goldsmith, Michael E. Brier, & George R. Aronoff. (2010). Iron, Inflammation, Dialysis Adequacy, Nutritional Status, and Hyperparathyroidism Modify Erythropoietic Response. Clinical Journal of the American Society of Nephrology. 5(4). 576–581. 57 indexed citations
15.
Brier, Michael E., Adam E. Gawęda, Andrew T. Dailey, George R. Aronoff, & Alfred A. Jacobs. (2010). Randomized Trial of Model Predictive Control for Improved Anemia Management. Clinical Journal of the American Society of Nephrology. 5(5). 814–820. 42 indexed citations
16.
Gawęda, Adam E., Brian H. Nathanson, Alfred A. Jacobs, et al.. (2010). Determining Optimum Hemoglobin Sampling for Anemia Management from Every-Treatment Data. Clinical Journal of the American Society of Nephrology. 5(11). 1939–1945. 19 indexed citations
17.
Gawęda, Adam E.. (2009). Improving management of Anemia in End Stage Renal Disease using Reinforcement Learning. 953–958. 5 indexed citations
18.
Gawęda, Adam E., Mehmet K. Muezzinoglu, George R. Aronoff, et al.. (2007). Using clinical information in goal-oriented learning. IEEE Engineering in Medicine and Biology Magazine. 26(2). 27–36. 2 indexed citations
19.
Gawęda, Adam E., Mehmet K. Muezzinoglu, Alfred A. Jacobs, George R. Aronoff, & Michael E. Brier. (2006). Model Predictive Control with Reinforcement Learning for Drug Delivery in Renal Anemia Management. PubMed. 2006. 5177–5180. 22 indexed citations
20.
Gawęda, Adam E., Mehmet K. Muezzinoglu, George R. Aronoff, et al.. (2005). Individualization of pharmacological anemia management using reinforcement learning. Neural Networks. 18(5-6). 826–834. 50 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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