Kevin S. King

2.9k total citations · 1 hit paper
54 papers, 2.1k citations indexed

About

Kevin S. King is a scholar working on Radiology, Nuclear Medicine and Imaging, Cardiology and Cardiovascular Medicine and Psychiatry and Mental health. According to data from OpenAlex, Kevin S. King has authored 54 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Radiology, Nuclear Medicine and Imaging, 17 papers in Cardiology and Cardiovascular Medicine and 12 papers in Psychiatry and Mental health. Recurrent topics in Kevin S. King's work include Cardiovascular Health and Disease Prevention (14 papers), Advanced MRI Techniques and Applications (12 papers) and Advanced Neuroimaging Techniques and Applications (11 papers). Kevin S. King is often cited by papers focused on Cardiovascular Health and Disease Prevention (14 papers), Advanced MRI Techniques and Applications (12 papers) and Advanced Neuroimaging Techniques and Applications (11 papers). Kevin S. King collaborates with scholars based in United States, United Kingdom and Spain. Kevin S. King's co-authors include Kenneth S. Kosik, Christine P. Donahue, Anna M. Krichevsky, Konstantin Khrapko, Ronald M. Peshock, Roderick McColl, Michael G. Harrington, Robert A. Kloner, Colby Ayers and Keith Hulsey and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Circulation and SHILAP Revista de lepidopterología.

In The Last Decade

Kevin S. King

53 papers receiving 2.1k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

A microRNA array reveals extensive regulation of microRNAs during brain development

2003 844 citations Kevin S. King et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Kevin S. King United States	20	848	679	390	264	220	54	2.1k
Jangsup Moon South Korea	32	739 0.9×	329 0.5×	239 0.6×	106 0.4×	208 0.9×	166	3.4k
Creed M. Stary United States	28	875 1.0×	511 0.8×	476 1.2×	48 0.2×	305 1.4×	77	2.4k
Yirong Yang United States	21	541 0.6×	325 0.5×	65 0.2×	129 0.5×	181 0.8×	60	1.9k
Xiao Wang China	23	306 0.4×	186 0.3×	176 0.5×	267 1.0×	279 1.3×	119	1.8k
Lawrence M. Shuer United States	20	1.4k 1.7×	252 0.4×	74 0.2×	130 0.5×	443 2.0×	45	3.5k
Andreas Bartsch Germany	13	337 0.4×	227 0.3×	111 0.3×	260 1.0×	96 0.4×	27	1.5k
Takehiko Adachi Japan	27	350 0.4×	277 0.4×	143 0.4×	54 0.2×	351 1.6×	76	1.8k
Konstantin Prass Germany	25	1.1k 1.3×	259 0.4×	154 0.4×	98 0.4×	387 1.8×	34	4.6k
Antonio Gutiérrez United States	18	350 0.4×	78 0.1×	190 0.5×	185 0.7×	222 1.0×	44	2.0k
H. Fred Downey United States	30	433 0.5×	140 0.2×	1.2k 3.1×	491 1.9×	595 2.7×	155	3.3k

Countries citing papers authored by Kevin S. King

Since Specialization

Citations

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

Fields of papers citing papers by Kevin S. King

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kevin S. King. 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 Kevin S. King. The network helps show where Kevin S. King may publish in the future.

Co-authorship network of co-authors of Kevin S. King

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

All Works

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20 of 20 papers shown

Tubi, Meral A., Wendy J. Mack, Helena C. Chui, et al.. (2023). White matter hyperintensity volume modifies the association between CSF vascular inflammatory biomarkers and regional FDG-PET along the Alzheimer’s disease continuum. Neurobiology of Aging. 132. 1–12. 1 indexed citations

Aghilinejad, Arian, et al.. (2023). Mechanistic insights on age-related changes in heart-aorta-brain hemodynamic coupling using a pulse wave model of the entire circulatory system. American Journal of Physiology-Heart and Circulatory Physiology. 325(5). H1193–H1209. 8 indexed citations

Borzage, Matthew, et al.. (2021). The First Examination of Diagnostic Performance of Automated Measurement of the Callosal Angle in 1856 Elderly Patients and Volunteers Indicates That 12.4% of Exams Met the Criteria for Possible Normal Pressure Hydrocephalus. American Journal of Neuroradiology. 42(11). 1942–1948. 12 indexed citations

Wei, Ke, et al.. (2021). Regional brain volumes relate to Alzheimer’s disease cerebrospinal fluid biomarkers and neuropsychometry: A cross-sectional, observational study. PLoS ONE. 16(7). e0254332–e0254332. 5 indexed citations

Coenen, Wilfried, Ernesto Criado-Hidalgo, Ke Wei, et al.. (2021). Transmantle Pressure Computed from MR Imaging Measurements of Aqueduct Flow and Dimensions. American Journal of Neuroradiology. 42(10). 1815–1821. 6 indexed citations

King, Kevin S., et al.. (2020). The association of nadir CD4-T cell count and endothelial dysfunction in a healthy HIV cohort without major cardiovascular risk factors. SHILAP Revista de lepidopterología. 8. 2107996892–2107996892. 9 indexed citations

Wei, Ke, Thao Tran, Patrick Chang, et al.. (2020). MRI Automated T1 Signal Intensity Detection of Diffuse Brain Manganese Accumulation in Cirrhosis. Journal of Neuroimaging. 31(1). 186–191. 1 indexed citations

Castor, Katherine, Shrutakirthi D Shenoi, Thao Tran, et al.. (2020). Urine dicarboxylic acids change in pre-symptomatic Alzheimer’s disease and reflect loss of energy capacity and hippocampal volume. PLoS ONE. 15(4). e0231765–e0231765. 12 indexed citations

Arakaki, Xianghong, Ke Wei, Thao Tran, et al.. (2020). Correlation of Neural Oscillations during Stroop Testing with Hippocampal and Amygdala Volume differ between Cognitively Healthy Normal Aging and Pre‐symptomatic Alzheimer’s Disease. The FASEB Journal. 34(S1). 1–1. 1 indexed citations

10.

Petersen, Melissa, James Hall, Leigh Johnson, et al.. (2020). Plasma neurofilament light chain (NFL) is differentially associated with neuropsychological test performance among non‐Hispanic whites and hispanic, Mexican Americans: A HABLE study. Alzheimer s & Dementia. 16(S4). 1 indexed citations

11.

Wei, Ke, Thao Tran, Matthew Borzage, et al.. (2019). White matter hypointensities and hyperintensities have equivalent correlations with age and CSF β‐amyloid in the nondemented elderly. Brain and Behavior. 9(12). e01457–e01457. 51 indexed citations

12.

Coenen, Wilfried, C. Gutiérrez-Montes, Ernesto Criado-Hidalgo, et al.. (2019). Subject-Specific Studies of CSF Bulk Flow Patterns in the Spinal Canal: Implications for the Dispersion of Solute Particles in Intrathecal Drug Delivery. American Journal of Neuroradiology. 40(7). 1242–1249. 22 indexed citations

13.

Tubi, Meral A., et al.. (2019). White matter hyperintensities and their relationship to cognition: Effects of segmentation algorithm. NeuroImage. 206. 116327–116327. 48 indexed citations

14.

Arakaki, Xianghong, Ryan Lee, Kevin S. King, Alfred N. Fonteh, & Michael G. Harrington. (2019). Alpha desynchronization during simple working memory unmasks pathological aging in cognitively healthy individuals. PLoS ONE. 14(1). e0208517–e0208517. 18 indexed citations

15.

Havakuk, Ofer, Kevin S. King, Luanda Grazette, et al.. (2017). Heart Failure-Induced Brain Injury. Journal of the American College of Cardiology. 69(12). 1609–1616. 99 indexed citations

16.

Goel, Akshay, Christopher D. Maroules, Gary F. Mitchell, et al.. (2016). Ethnic Difference in Proximal Aortic Stiffness. JACC. Cardiovascular imaging. 10(1). 54–61. 37 indexed citations

17.

Lucatelli, Pierleone, Eytan Raz, Luca Saba, et al.. (2016). Relationship between leukoaraiosis, carotid intima-media thickness and intima-media thickness variability: Preliminary results. European Radiology. 26(12). 4423–4431. 19 indexed citations

18.

Peshock, Ronald M., Roderick McColl, Keith Hulsey, et al.. (2012). MR Imaging of Hippocampal Asymmetry at 3T in a Multiethnic, Population-Based Sample: Results from the Dallas Heart Study. American Journal of Neuroradiology. 34(4). 752–757. 36 indexed citations

19.

King, Kevin S., Ronald M. Peshock, Matthew Warren, et al.. (2012). Evaluation of a Practical Visual MRI Rating Scale of Brain White Matter Hyperintensities for Clinicians Based on Largest Lesion Size Regardless of Location. American Journal of Neuroradiology. 34(4). 797–801. 8 indexed citations

20.

Urayama, Akihiko, et al.. (2006). Effects of chronic ethanol administration on brain interstitial fluid levels of Methionine-enkephalin as measured by microdialysis in vivo. Peptides. 27(9). 2201–2206. 6 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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