Brian C. Dean

1.5k total citations
50 papers, 785 citations indexed

About

Brian C. Dean is a scholar working on Cognitive Neuroscience, Psychiatry and Mental health and Computer Networks and Communications. According to data from OpenAlex, Brian C. Dean has authored 50 papers receiving a total of 785 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Cognitive Neuroscience, 10 papers in Psychiatry and Mental health and 9 papers in Computer Networks and Communications. Recurrent topics in Brian C. Dean's work include Epilepsy research and treatment (9 papers), EEG and Brain-Computer Interfaces (8 papers) and Complexity and Algorithms in Graphs (7 papers). Brian C. Dean is often cited by papers focused on Epilepsy research and treatment (9 papers), EEG and Brain-Computer Interfaces (8 papers) and Complexity and Algorithms in Graphs (7 papers). Brian C. Dean collaborates with scholars based in United States, United Kingdom and Qatar. Brian C. Dean's co-authors include Jan Vondrák, Michel X. Goemans, M. X. Goemans, Jonathan J. Halford, J. Vondrák, Ekrem Kutluay, Gabriel U. Martz, Amir Arain, Robert J. Schalkoff and Suzette M. LaRoche and has published in prestigious journals such as Clinical Pharmacology & Therapeutics, Clinical Neurophysiology and Medical Image Analysis.

In The Last Decade

Brian C. Dean

49 papers receiving 746 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Brian C. Dean United States 14 231 213 181 120 106 50 785
Jean Dollimore United Kingdom 9 121 0.5× 726 3.4× 34 0.2× 26 0.2× 50 0.5× 20 1.2k
M. J. Ebadi Iran 17 136 0.6× 69 0.3× 51 0.3× 14 0.1× 52 0.5× 45 862
Heli Sun China 21 54 0.2× 214 1.0× 30 0.2× 21 0.2× 35 0.3× 88 1.6k
Xuemei Ding United Kingdom 16 51 0.2× 63 0.3× 94 0.5× 14 0.1× 49 0.5× 43 793
Gurvinder Singh India 21 45 0.2× 345 1.6× 111 0.6× 41 0.3× 51 0.5× 114 1.4k
Dilip Singh Sisodia India 19 308 1.3× 128 0.6× 35 0.2× 7 0.1× 48 0.5× 93 1.7k
Muhammad Usman Pakistan 17 179 0.8× 47 0.2× 68 0.4× 10 0.1× 21 0.2× 59 863
Vineet Gupta United States 22 99 0.4× 140 0.7× 21 0.1× 12 0.1× 37 0.3× 67 1.2k
Zheng Xiao China 14 61 0.3× 76 0.4× 92 0.5× 22 0.2× 16 0.2× 54 786
Bo Jin China 19 116 0.5× 74 0.3× 8 0.0× 14 0.1× 43 0.4× 86 1.2k

Countries citing papers authored by Brian C. Dean

Since Specialization
Citations

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

Fields of papers citing papers by Brian C. Dean

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Brian C. Dean. 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 Brian C. Dean. The network helps show where Brian C. Dean may publish in the future.

Co-authorship network of co-authors of Brian C. Dean

This figure shows the co-authorship network connecting the top 25 collaborators of Brian C. Dean. A scholar is included among the top collaborators of Brian C. Dean 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 Brian C. Dean. Brian C. Dean 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.
Mandlekar, Sandhya, Dhruvitkumar S. Sutaria, Yixuan Zou, et al.. (2024). Evaluation of Patient‐Centric Sample Collection Technologies for Pharmacokinetic Assessment of Large and Small Molecules. Clinical Pharmacology & Therapeutics. 116(3). 782–794. 4 indexed citations
2.
Welch, Brandon M., Caitlin G. Allen, Lewis J. Frey, et al.. (2021). Comparison of a Cancer Family History Collection and Risk Assessment Tool – ItRunsInMyFamily – with Risk Assessment by Health-Care Professionals. Public Health Genomics. 25(3-4). 80–88. 3 indexed citations
3.
Joseph, Jane E., Xun Zhu, Mulugeta Gebregziabher, et al.. (2018). Tracking the Development of Functional Connectomes for Face Processing. Brain Connectivity. 9(2). 231–239.
4.
Dauwels, Justin, et al.. (2017). Interictal epileptiform discharge characteristics underlying expert interrater agreement. Clinical Neurophysiology. 128(10). 1994–2005. 30 indexed citations
5.
Foreman, Brandon, Prasanna Tadi, Jan Claassen, et al.. (2015). Generalized periodic discharges and ‘triphasic waves’: A blinded evaluation of inter-rater agreement and clinical significance. Clinical Neurophysiology. 127(2). 1073–1080. 57 indexed citations
6.
Halford, Jonathan J., Deng‐Shan Shiau, Brad J. Kolls, et al.. (2014). Inter-rater agreement on identification of electrographic seizures and periodic discharges in ICU EEG recordings. Clinical Neurophysiology. 126(9). 1661–1669. 47 indexed citations
7.
Wood, Scott T., Brian C. Dean, & Delphine Dean. (2013). A linear programming approach to reconstructing subcellular structures from confocal images for automated generation of representative 3D cellular models. Medical Image Analysis. 17(3). 337–347. 8 indexed citations
8.
Wood, Scott T., Brian C. Dean, & Delphine Dean. (2012). A Computational Approach to Understand Phenotypic Structure and Constitutive Mechanics Relationships of Single Cells. Annals of Biomedical Engineering. 41(3). 630–644. 4 indexed citations
9.
Halford, Jonathan J., Robert J. Schalkoff, Selim R. Benbadis, et al.. (2012). Standardized database development for EEG epileptiform transient detection: EEGnet scoring system and machine learning analysis. Journal of Neuroscience Methods. 212(2). 308–316. 50 indexed citations
10.
Schalkoff, Robert J., et al.. (2012). Morphology-based wavelet features and multiple mother wavelet strategy for spike classification in EEG signals. PubMed. 2012. 3959–3962. 7 indexed citations
11.
Halford, Jonathan J., Selim R. Benbadis, William O. Tatum, et al.. (2011). Web-Based Collection of Expert Opinion on Routine Scalp EEG: Software Development and Interrater Reliability. Journal of Clinical Neurophysiology. 28(2). 178–184. 21 indexed citations
12.
Dean, Brian C.. (2010). Speeding up Stochastic Dynamic Programming with Zero-Delay Convolution. 5(2). 96–104. 6 indexed citations
13.
Dean, Brian C., et al.. (2008). A linear‐time algorithm for broadcast domination in a tree. Networks. 53(2). 160–169. 12 indexed citations
14.
Dean, Brian C.. (2005). A simple expected running time analysis for randomized “divide and conquer” algorithms. Discrete Applied Mathematics. 154(1). 1–5. 11 indexed citations
15.
Dean, Brian C.. (2004). Algorithms for minimum‐cost paths in time‐dependent networks with waiting policies. Networks. 44(1). 41–46. 49 indexed citations
16.
Kim, Katherine J., et al.. (1999). Novel copolymers of trisubstituted ethylenes and styrene- 5. Ring-disubstituted methyl 2-cyano-3-phenyl-2-propenoates. Designed Monomers & Polymers. 2(4). 333–341. 8 indexed citations
17.
Dean, Brian C.. (1999). Continuous-Time Dynamic Shortest Path Algorithms. 31 indexed citations
18.
19.
McLellan, D L & Brian C. Dean. (1982). Improved control of brittle Parkinsonism by separate administration of levodopa and benserazide.. BMJ. 284(6321). 1001–1002. 6 indexed citations
20.
Magnus, R., Brian C. Dean, & Stephen H. Curry. (1977). Clorazepate: double blind crossover comparison of a single nightly dose with diazepam thrice daily in anxiety.. Munich Personal RePEc Archive (Ludwig Maximilian University of Munich). 38(10). 819–21. 8 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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