Ted M. Burns

8.6k total citations · 1 hit paper
91 papers, 3.6k citations indexed

About

Ted M. Burns is a scholar working on Neurology, Cellular and Molecular Neuroscience and Physiology. According to data from OpenAlex, Ted M. Burns has authored 91 papers receiving a total of 3.6k indexed citations (citations by other indexed papers that have themselves been cited), including 65 papers in Neurology, 19 papers in Cellular and Molecular Neuroscience and 13 papers in Physiology. Recurrent topics in Ted M. Burns's work include Peripheral Neuropathies and Disorders (40 papers), Myasthenia Gravis and Thymoma (34 papers) and Parkinson's Disease and Spinal Disorders (20 papers). Ted M. Burns is often cited by papers focused on Peripheral Neuropathies and Disorders (40 papers), Myasthenia Gravis and Thymoma (34 papers) and Parkinson's Disease and Spinal Disorders (20 papers). Ted M. Burns collaborates with scholars based in United States, United Kingdom and Italy. Ted M. Burns's co-authors include Donald B. Sanders, Mark R. Conaway, Socrates J. Tzartos, Amelia Evoli, Jacqueline Palace, Nils Erik Gilhus, Jan J.G.M. Verschuuren, Gary Cutter, Kelly Gwathmey and P. James B. Dyck and has published in prestigious journals such as PLoS ONE, Neurology and Annals of Neurology.

In The Last Decade

Ted M. Burns

88 papers receiving 3.5k citations

Hit Papers

Myasthenia gravis 2019 2026 2021 2023 2019 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ted M. Burns United States 33 2.9k 531 374 369 327 91 3.6k
Richard J. Barohn United States 37 4.5k 1.6× 950 1.8× 625 1.7× 276 0.7× 314 1.0× 114 6.1k
Laura Herbelin United States 20 1.4k 0.5× 212 0.4× 252 0.7× 219 0.6× 346 1.1× 56 2.3k
Wilson W. Bryan United States 32 2.4k 0.8× 235 0.4× 798 2.1× 246 0.7× 788 2.4× 46 4.1k
Nancy L. Kuntz United States 28 1.9k 0.7× 390 0.7× 242 0.6× 170 0.5× 521 1.6× 102 3.5k
David S. Younger United States 25 1.4k 0.5× 107 0.2× 220 0.6× 388 1.1× 212 0.6× 114 2.5k
Carlo Antozzi Italy 37 2.2k 0.8× 513 1.0× 396 1.1× 132 0.4× 218 0.7× 138 4.3k
Michael Nicolle Canada 24 2.2k 0.8× 451 0.8× 240 0.6× 74 0.2× 105 0.3× 58 3.1k
Miriam Freimer United States 24 1.3k 0.4× 105 0.2× 778 2.1× 420 1.1× 146 0.4× 58 2.2k
Cheng‐Hong Toh Taiwan 27 546 0.2× 213 0.4× 442 1.2× 104 0.3× 457 1.4× 91 2.4k
Heather E. Moss United States 24 1.6k 0.6× 128 0.2× 227 0.6× 167 0.5× 62 0.2× 141 2.8k

Countries citing papers authored by Ted M. Burns

Since Specialization
Citations

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

Fields of papers citing papers by Ted M. Burns

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ted M. Burns. 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 Ted M. Burns. The network helps show where Ted M. Burns may publish in the future.

Co-authorship network of co-authors of Ted M. Burns

This figure shows the co-authorship network connecting the top 25 collaborators of Ted M. Burns. A scholar is included among the top collaborators of Ted M. Burns 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 Ted M. Burns. Ted M. Burns 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.
Hehir, Michael K., Mark R. Conaway, Noah Kolb, et al.. (2023). Measuring treatment adverse event burden in myasthenia gravis: Single‐center prospective evaluation utilizing the Adverse Event Unit (AEU). Muscle & Nerve. 69(1). 32–39. 3 indexed citations
2.
Hehir, Michael K., Mark R. Conaway, Eric M. Clark, et al.. (2022). The Adverse Event Unit (AEU): A novel metric to measure the burden of treatment adverse events. PLoS ONE. 17(2). e0262109–e0262109. 4 indexed citations
3.
4.
Bjelica, Bogdan, Stojan Perić, Kelly Gwathmey, et al.. (2019). Chronic Acquired Polyneuropathy Patient Reported Index (CAPPRI) in chronic inflammatory demyelinating polyradiculoneuropathy. Journal of the Peripheral Nervous System. 24(3). 247–252. 6 indexed citations
5.
Hehir, Michael K., Lisa D. Hobson‐Webb, Michael Benatar, et al.. (2017). Rituximab as treatment for anti-MuSK myasthenia gravis. Neurology. 89(10). 1069–1077. 166 indexed citations
6.
Ballow, Mark, Mark R. Conaway, Rima Rachid, et al.. (2016). Construction and Validation of a Health-Related Quality of Life (HR-QOL) Instrument for Patients with Primary Antibody Deficiency Disease. Journal of Allergy and Clinical Immunology. 137(2). AB221–AB221. 1 indexed citations
7.
Nagel, Maria A., Ted M. Burns, & Don Gilden. (2016). SUNCT headaches after ipsilateral ophthalmic-distribution zoster. Journal of the Neurological Sciences. 366. 207–208. 7 indexed citations
8.
Benatar, Michael, Donald B. Sanders, Ted M. Burns, et al.. (2012). Recommendations for myasthenia gravis clinical trials. Muscle & Nerve. 45(6). 909–917. 114 indexed citations
9.
Farrugia, Maria Elena, et al.. (2011). The oculobulbar facial respiratory score is a tool to assess bulbar function in myasthenia gravis patients. Muscle & Nerve. 43(3). 329–334. 9 indexed citations
10.
Gwathmey, Kelly, Rasheed A. Balogun, & Ted M. Burns. (2011). Neurologic indications for therapeutic plasma exchange: An update. Journal of Clinical Apheresis. 26(5). 261–268. 13 indexed citations
11.
Sadjadi, Reza, et al.. (2011). Psychometric evaluation of the myasthenia gravis composite using rasch analysis. Muscle & Nerve. 45(6). 820–825. 18 indexed citations
12.
Muppidi, Srikanth, et al.. (2011). MG‐ADL: Still a relevant outcome measure. Muscle & Nerve. 44(5). 727–731. 112 indexed citations
13.
Balogun, Rasheed A., André A. Kaplan, David M. Ward, et al.. (2010). Clinical applications of therapeutic apheresis. Journal of Clinical Apheresis. 25(5). 250–264. 18 indexed citations
14.
Burns, Ted M., et al.. (2008). Less is more, or almost as much: A 15‐item quality‐of‐life instrument for myasthenia gravis. Muscle & Nerve. 38(2). 957–963. 149 indexed citations
15.
Burns, Ted M., et al.. (2007). Stiff-person syndrome. Current Treatment Options in Neurology. 9(3). 234–240. 14 indexed citations
16.
Burns, Ted M., René H. M. te Morsche, Jan B.�M.�J. Jansen, & Joost P.H. Drenth. (2005). Genetic heterogeneity and exclusion of a modifying locus at 2q in a family with autosomal dominant primary erythermalgia. British Journal of Dermatology. 153(1). 174–177. 21 indexed citations
17.
Kang, Peter B., et al.. (2004). Multifocal slowing of nerve conduction in metachromatic leukodystrophy. Muscle & Nerve. 29(4). 531–536. 21 indexed citations
18.
Burns, Ted M., et al.. (2002). Clinical versus quantitative vibration assessment: improving clinical performance. Journal of the Peripheral Nervous System. 7(2). 112–117. 17 indexed citations
19.
Burns, Ted M., et al.. (1988). Linkage between the loci for autosomal dominant neuronal Charcot-Marie-Tooth neuropathy (CMT1) and serum amyloid P component (APCS) on human chromosome 1. Cytogenetic and Genome Research. 47(3). 175–176. 1 indexed citations
20.
Ionâşescu, Victor, et al.. (1988). Linkage between the loci for autosomal dominant Charcot-Marie-Tooth neuropathy type 1 and human glucocerebrosidase. Cytogenetic and Genome Research. 47(3). 173–174. 1 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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