Joost Raaphorst

3.9k total citations
77 papers, 1.8k citations indexed

About

Joost Raaphorst is a scholar working on Neurology, Epidemiology and Cellular and Molecular Neuroscience. According to data from OpenAlex, Joost Raaphorst has authored 77 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 49 papers in Neurology, 27 papers in Epidemiology and 17 papers in Cellular and Molecular Neuroscience. Recurrent topics in Joost Raaphorst's work include Amyotrophic Lateral Sclerosis Research (26 papers), Inflammatory Myopathies and Dermatomyositis (25 papers) and Parkinson's Disease Mechanisms and Treatments (20 papers). Joost Raaphorst is often cited by papers focused on Amyotrophic Lateral Sclerosis Research (26 papers), Inflammatory Myopathies and Dermatomyositis (25 papers) and Parkinson's Disease Mechanisms and Treatments (20 papers). Joost Raaphorst collaborates with scholars based in Netherlands, United States and United Kingdom. Joost Raaphorst's co-authors include Marianne de Visser, Ben Schmand, Rob J. de Haan, Emma Beeldman, Baziel G.M. van Engelen, Anneke J. van der Kooi, M. Klein Twennaar, Kees Okkersen, Wim H.J.P. Linssen and Leonard H. van den Berg and has published in prestigious journals such as JAMA, Neurology and The Lancet Neurology.

In The Last Decade

Joost Raaphorst

72 papers receiving 1.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Joost Raaphorst Netherlands 26 1.1k 434 425 364 321 77 1.8k
Flavio Giordano Italy 26 781 0.7× 320 0.7× 337 0.8× 350 1.0× 235 0.7× 137 2.3k
Carmel Armon United States 27 1.6k 1.5× 338 0.8× 432 1.0× 620 1.7× 185 0.6× 77 2.7k
Neil Schwartz United States 20 506 0.5× 338 0.8× 379 0.9× 246 0.7× 267 0.8× 47 2.1k
Wolfgang N. Löscher Austria 28 722 0.7× 500 1.2× 636 1.5× 177 0.5× 201 0.6× 125 2.8k
Ron Dabby Israel 23 625 0.6× 415 1.0× 357 0.8× 142 0.4× 248 0.8× 65 1.8k
Lundy Day Canada 10 491 0.5× 730 1.7× 522 1.2× 214 0.6× 142 0.4× 16 2.1k
Stefano Zoccolella Italy 24 1.3k 1.2× 357 0.8× 178 0.4× 510 1.4× 186 0.6× 78 1.9k
Franco Gemignani Italy 27 1.2k 1.1× 289 0.7× 741 1.7× 163 0.4× 396 1.2× 78 2.0k
Dario Cocito Italy 26 1.6k 1.5× 140 0.3× 925 2.2× 237 0.7× 563 1.8× 70 2.7k
Martijn R. Tannemaat Netherlands 28 627 0.6× 321 0.7× 792 1.9× 97 0.3× 255 0.8× 92 2.2k

Countries citing papers authored by Joost Raaphorst

Since Specialization
Citations

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

Fields of papers citing papers by Joost Raaphorst

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Joost Raaphorst. 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 Joost Raaphorst. The network helps show where Joost Raaphorst may publish in the future.

Co-authorship network of co-authors of Joost Raaphorst

This figure shows the co-authorship network connecting the top 25 collaborators of Joost Raaphorst. A scholar is included among the top collaborators of Joost Raaphorst 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 Joost Raaphorst. Joost Raaphorst 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.
Beeldman, Emma, Matteo Fraschini, Alessandra Griffa, et al.. (2025). Longitudinal changes in MEG-based brain network topology of ALS patients with cognitive/behavioral impairment—An exploratory study. Network Neuroscience. 9(3). 824–841. 1 indexed citations
2.
Raaphorst, Joost, Anneke J. van der Kooi, Christopher A. Mecoli, et al.. (2025). Advances in the classification and management of idiopathic inflammatory myopathies. The Lancet Neurology. 24(9). 776–788. 2 indexed citations
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Saygın, Didem, Helene Alexanderson, Dana DiRenzo, et al.. (2024). The impact of pain on daily activities in patients with idiopathic inflammatory myopathies: Report from the OMERACT myositis working group. Seminars in Arthritis and Rheumatism. 67. 152476–152476. 2 indexed citations
6.
Veldkamp, Saskia R, Johan Lim, Annet van Royen‐Kerkhof, et al.. (2024). Type I interferon biomarker in idiopathic inflammatory myopathies: associations of Siglec-1 with disease activity and treatment response. Lara D. Veeken. 64(5). 2979–2986. 4 indexed citations
7.
Leeuwen, Ester M. van, Anneke J. van der Kooi, Kyra A. Gelderman, et al.. (2023). Does COVID-19 impact the prevalence of myositis specific antibodies in the Netherlands? A comparative nationwide study. Journal of Autoimmunity. 139. 103081–103081. 2 indexed citations
8.
Stunnenberg, Bas C., Robert C. Griggs, Jeffrey Statland, et al.. (2021). N-of-1 Trials in Neurology. Neurology. 98(2). e174–e185. 8 indexed citations
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Thielen, Jordy, et al.. (2021). A visual brain-computer interface as communication aid for patients with amyotrophic lateral sclerosis. Clinical Neurophysiology. 132(10). 2404–2415. 28 indexed citations
11.
Raaphorst, Joost, et al.. (2021). New Insights in Adherence and Survival in Myotonic Dystrophy Patients Using Home Mechanical Ventilation. Respiration. 100(2). 154–163. 10 indexed citations
12.
Okkersen, Kees, Nens van Alfen, Roy P. C. Kessels, et al.. (2020). Characterization of EEG-based functional brain networks in myotonic dystrophy type 1. Clinical Neurophysiology. 131(8). 1886–1895. 3 indexed citations
13.
Mollink, Jeroen, Karla L. Miller, Mark Jenkinson, et al.. (2019). White matter changes in the perforant path area in patients with amyotrophic lateral sclerosis. Neuropathology and Applied Neurobiology. 45(6). 570–585. 22 indexed citations
14.
Okkersen, Kees, et al.. (2019). Affective symptoms and apathy in myotonic dystrophy type 1 a systematic review and meta-analysis. Journal of Affective Disorders. 250. 260–269. 25 indexed citations
15.
Seelen, Meinie, Jan H. Veldink, Anne E Visser, et al.. (2017). Long-Term Air Pollution Exposure and Amyotrophic Lateral Sclerosis in Netherlands: A Population-based Case–control Study. Environmental Health Perspectives. 125(9). 97023–97023. 64 indexed citations
16.
Visser, Anne E, Raha Pazoki, Sara L. Pulit, et al.. (2017). No association between gluten sensitivity and amyotrophic lateral sclerosis. Journal of Neurology. 264(4). 694–700. 4 indexed citations
17.
Groothuis, Jan T., Thijs Feuth, Yvonne F. Heijdra, et al.. (2017). The predictive value of respiratory function tests for non-invasive ventilation in amyotrophic lateral sclerosis. Respiratory Research. 18(1). 144–144. 57 indexed citations
18.
Stunnenberg, Bas C., Willem Woertman, Joost Raaphorst, et al.. (2015). Combined N-of-1 trials to investigate mexiletine in non-dystrophic myotonia using a Bayesian approach; study rationale and protocol. BMC Neurology. 15(1). 43–43. 18 indexed citations
19.
Beeldman, Emma, Bregje Jaeger, Joost Raaphorst, et al.. (2014). The verbal fluency index: Dutch normative data for cognitive testing in ALS. Amyotrophic Lateral Sclerosis and Frontotemporal Degeneration. 15(5-6). 388–391. 14 indexed citations
20.
Raaphorst, Joost, Emma Beeldman, Marianne de Visser, Rob J. de Haan, & Ben Schmand. (2012). A systematic review of behavioural changes in motor neuron disease. Amyotrophic Lateral Sclerosis. 13(6). 493–501. 62 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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