Richard L. Goodwin

2.4k total citations
80 papers, 1.4k citations indexed

About

Richard L. Goodwin is a scholar working on Molecular Biology, Surgery and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Richard L. Goodwin has authored 80 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Molecular Biology, 20 papers in Surgery and 17 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Richard L. Goodwin's work include Congenital heart defects research (13 papers), Tissue Engineering and Regenerative Medicine (12 papers) and Cardiac Valve Diseases and Treatments (11 papers). Richard L. Goodwin is often cited by papers focused on Congenital heart defects research (13 papers), Tissue Engineering and Regenerative Medicine (12 papers) and Cardiac Valve Diseases and Treatments (11 papers). Richard L. Goodwin collaborates with scholars based in United States, China and United Kingdom. Richard L. Goodwin's co-authors include Michael J. Yost, Jay D. Potts, Mani T. Valarmathi, Robert L. Price, Roger R. Markwald, Russell A. Norris, Jeffrey Davis, Heather J. Evans‐Anderson, Heinz Baumann and M Hart and has published in prestigious journals such as Journal of Biological Chemistry, SHILAP Revista de lepidopterología and Biomaterials.

In The Last Decade

Richard L. Goodwin

71 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Richard L. Goodwin United States 21 670 342 337 228 213 80 1.4k
Roman Schoenauer Switzerland 19 564 0.8× 268 0.8× 382 1.1× 90 0.4× 182 0.9× 27 1.1k
Camie W. Chan United States 21 727 1.1× 460 1.3× 188 0.6× 282 1.2× 129 0.6× 35 1.8k
Nicole L. Rosin Canada 19 467 0.7× 155 0.5× 171 0.5× 121 0.5× 134 0.6× 34 1.4k
Vishal Nigam United States 20 1.1k 1.6× 623 1.8× 597 1.8× 255 1.1× 220 1.0× 49 2.2k
Kentaro Ishida Japan 16 777 1.2× 290 0.8× 236 0.7× 329 1.4× 80 0.4× 82 1.8k
William A. LaFramboise United States 27 963 1.4× 324 0.9× 305 0.9× 183 0.8× 53 0.2× 96 2.0k
Danielle E. Dye Australia 24 952 1.4× 141 0.4× 517 1.5× 121 0.5× 88 0.4× 46 1.6k
John Wardale United Kingdom 20 588 0.9× 309 0.9× 462 1.4× 167 0.7× 186 0.9× 25 1.4k
Alfred C. Kuo United States 29 1.0k 1.5× 1.1k 3.1× 126 0.4× 155 0.7× 113 0.5× 54 2.7k

Countries citing papers authored by Richard L. Goodwin

Since Specialization
Citations

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

Fields of papers citing papers by Richard L. Goodwin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Richard L. Goodwin. 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 Richard L. Goodwin. The network helps show where Richard L. Goodwin may publish in the future.

Co-authorship network of co-authors of Richard L. Goodwin

This figure shows the co-authorship network connecting the top 25 collaborators of Richard L. Goodwin. A scholar is included among the top collaborators of Richard L. Goodwin 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 Richard L. Goodwin. Richard L. Goodwin 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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Goodwin, Richard L., et al.. (2024). Comorbidities in patients with vascular dementia and Alzheimer's disease with Neuropsychiatric symptoms. Geriatric Nursing. 57. 217–223. 3 indexed citations
5.
Parker, Patti C., et al.. (2023). Prediction of Pelvic Organ Prolapse Postsurgical Outcome Using Biomaterial-Induced Blood Cytokine Levels: Machine Learning Approach. SHILAP Revista de lepidopterología. 6. e40402–e40402.
6.
Goodwin, Richard L. & Thomas I. Nathaniel. (2023). Effective Feedback Strategy for Formative Assessment in an Integrated Medical Neuroscience Course. Medical Science Educator. 33(3). 747–753. 4 indexed citations
7.
Goodwin, Richard L., et al.. (2022). Age Stratification in Acute Ischemic Stroke Patients with Heart Failure. Journal of Clinical Medicine. 12(1). 38–38. 4 indexed citations
8.
Brown, Christina M., et al.. (2022). Stroke Severity in Ischemic Stroke Patients with a History of Diastolic Blood Pressure Treated in a Telestroke Network. Journal of Cardiovascular Development and Disease. 9(10). 345–345. 7 indexed citations
9.
Poupore, Nicolas, et al.. (2022). Gender Differences in Demographic and Pharmacological Factors in Patients Diagnosed with Late-Onset of Alzheimer’s Disease. Brain Sciences. 12(2). 160–160. 12 indexed citations
10.
Poupore, Nicolas, Renée J. Chosed, Sergio Arce, et al.. (2021). Metabolomic Profiles of Men and Women Ischemic Stroke Patients. Diagnostics. 11(10). 1786–1786. 13 indexed citations
11.
Kheradvar, Arash, Ramin Zareian, Shimako Kawauchi, Richard L. Goodwin, & Sandra Rugonyi. (2017). Animal models for heart valve research and development. Drug Discovery Today Disease Models. 24. 55–62. 20 indexed citations
12.
Eberth, John F., et al.. (2014). The impact of flow-induced forces on the morphogenesis of the outflow tract. Frontiers in Physiology. 5. 225–225. 27 indexed citations
13.
Wang, Ruikang K., Richard L. Goodwin, Roger R. Markwald, et al.. (2012). 4D imaging of embryonic chick hearts by streak-mode Fourier domain optical coherence tomography. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 8207. 82073V–82073V. 4 indexed citations
14.
Tan, Hong, et al.. (2010). Expression and Deposition of Fibrous Extracellular Matrix Proteins in Cardiac Valves during Chick Development. Microscopy and Microanalysis. 17(1). 91–100. 10 indexed citations
15.
Potts, Jay D., et al.. (2009). Mathematical Modeling of Flow-Generated Forces in an In Vitro System of Cardiac Valve Development. Annals of Biomedical Engineering. 38(1). 109–117. 14 indexed citations
16.
Valarmathi, Mani T., Michael J. Yost, Richard L. Goodwin, & Jay D. Potts. (2008). A Three-Dimensional Tubular Scaffold that Modulates the Osteogenic and Vasculogenic Differentiation of Rat Bone Marrow Stromal Cells. Tissue Engineering Part A. 14(4). 491–504. 26 indexed citations
17.
Valarmathi, Mani T., Michael J. Yost, Richard L. Goodwin, & Jay D. Potts. (2008). The influence of proepicardial cells on the osteogenic potential of marrow stromal cells in a three-dimensional tubular scaffold. Biomaterials. 29(14). 2203–2216. 28 indexed citations
18.
Evans‐Anderson, Heather J. & Richard L. Goodwin. (2007). Western array analysis of cell cycle protein changes during the hyperplastic to hypertrophic transition in heart development. Molecular and Cellular Biochemistry. 303(1-2). 189–199. 5 indexed citations
19.
Yost, Michael J., et al.. (2006). Epicardial Development in the Rat: A New Perspective. Microscopy and Microanalysis. 12(5). 390–398. 33 indexed citations
20.
Rheaume, Carol, et al.. (1994). Evolution of murine ?1-proteinase inhibitors: Gene amplification and reactive center divergence. Journal of Molecular Evolution. 38(2). 121–131. 16 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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