Nens van Alfen

8.0k total citations
176 papers, 4.9k citations indexed

About

Nens van Alfen is a scholar working on Surgery, Radiology, Nuclear Medicine and Imaging and Molecular Biology. According to data from OpenAlex, Nens van Alfen has authored 176 papers receiving a total of 4.9k indexed citations (citations by other indexed papers that have themselves been cited), including 69 papers in Surgery, 56 papers in Radiology, Nuclear Medicine and Imaging and 51 papers in Molecular Biology. Recurrent topics in Nens van Alfen's work include Peripheral Nerve Disorders (52 papers), Nerve Injury and Rehabilitation (44 papers) and Muscle Physiology and Disorders (42 papers). Nens van Alfen is often cited by papers focused on Peripheral Nerve Disorders (52 papers), Nerve Injury and Rehabilitation (44 papers) and Muscle Physiology and Disorders (42 papers). Nens van Alfen collaborates with scholars based in Netherlands, United States and Switzerland. Nens van Alfen's co-authors include Baziel G.M. van Engelen, Sigrid Pillen, Merel Jansen, Imelda J. M. de Groot, Juerd Wijntjes, Jan T. Groothuis, J.J.J. van Eijk, Machiel J. Zwarts, Alexander C. H. Geurts and Nicol C. Voermans and has published in prestigious journals such as PLoS ONE, Brain and Neurology.

In The Last Decade

Nens van Alfen

169 papers receiving 4.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Nens van Alfen Netherlands 40 1.8k 1.6k 1.1k 1.0k 618 176 4.9k
Michael S. Cartwright United States 38 2.2k 1.2× 2.1k 1.3× 1.3k 1.3× 251 0.2× 489 0.8× 140 4.7k
Sigrid Pillen Netherlands 33 807 0.4× 465 0.3× 735 0.7× 758 0.7× 346 0.6× 80 4.1k
G. Parry United Kingdom 40 1.6k 0.9× 640 0.4× 1.7k 1.7× 1.2k 1.2× 977 1.6× 181 6.3k
Frank Spaans Netherlands 30 1.2k 0.7× 897 0.6× 645 0.6× 562 0.6× 573 0.9× 65 3.1k
Jasper R. Daube United States 48 1.4k 0.8× 1.1k 0.7× 3.6k 3.4× 717 0.7× 1.9k 3.1× 154 6.8k
Roberto Floris Italy 32 638 0.4× 1.1k 0.7× 1.3k 1.2× 383 0.4× 342 0.6× 246 4.3k
Manoel Jacobsen Teixeira Brazil 46 1.6k 0.9× 699 0.4× 4.1k 3.9× 512 0.5× 1.4k 2.3× 667 9.8k
W. Trojaborg Denmark 37 781 0.4× 873 0.5× 1.9k 1.8× 553 0.5× 1.0k 1.7× 142 4.5k
Jens Dreyhaupt Germany 35 709 0.4× 902 0.6× 442 0.4× 615 0.6× 126 0.2× 167 4.7k
Byung‐Jo Kim South Korea 35 1.1k 0.6× 725 0.5× 1.2k 1.1× 179 0.2× 278 0.4× 198 3.5k

Countries citing papers authored by Nens van Alfen

Since Specialization
Citations

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

Fields of papers citing papers by Nens van Alfen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nens van Alfen. 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 Nens van Alfen. The network helps show where Nens van Alfen may publish in the future.

Co-authorship network of co-authors of Nens van Alfen

This figure shows the co-authorship network connecting the top 25 collaborators of Nens van Alfen. A scholar is included among the top collaborators of Nens van Alfen 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 Nens van Alfen. Nens van Alfen 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.
Alfen, Nens van, et al.. (2025). Machine learning-driven Heckmatt grading in facioscapulohumeral muscular dystrophy: A novel pathway for musculoskeletal ultrasound analysis. Clinical Neurophysiology. 172. 61–69. 1 indexed citations
2.
Alfen, Nens van, et al.. (2024). Islands and bridges in healthcare: the importance of general neurology. Practical Neurology. 24(6). 532–534.
3.
Hannaford, Andrew, et al.. (2024). Electrodiagnostic studies and new diagnostic modalities for evaluation of peripheral nerve disorders. Muscle & Nerve. 69(6). 653–669. 4 indexed citations
4.
Goselink, Rianne J.M., et al.. (2024). Longitudinal Insights Into Childhood Onset Facioscapulohumeral Dystrophy. Neurology. 104(1). e210059–e210059. 1 indexed citations
5.
Padberg, George W., et al.. (2024). The other face of facioscapulohumeral muscular dystrophy: Exploring orofacial weakness using muscle ultrasound. Muscle & Nerve. 70(5). 1062–1071. 2 indexed citations
6.
Hulst, Karen van, et al.. (2024). Quantitative ultrasound of submental and masticatory muscles in children with cerebral palsy. Journal of Pediatric Rehabilitation Medicine. 18(1). 13–22.
7.
Engel–Hoek, L. van den, et al.. (2023). Validity and reliability of visual assessment of orofacial muscle ultrasound images using a modified Heckmatt scale. Muscle & Nerve. 68(2). 176–183. 5 indexed citations
8.
Groothuis, Jan T., Jonne Doorduin, Nens van Alfen, et al.. (2023). LAMA2 -Related Muscular Dystrophy Across the Life Span. Neurology Genetics. 9(5). e200089–e200089. 14 indexed citations
9.
Cameron, Ian, Nens van Alfen, Ivan Toni, et al.. (2022). Cerebral Adaptation Associated with Peripheral Nerve Recovery in Neuralgic Amyotrophy: A Randomized Controlled Trial. Neurorehabilitation and neural repair. 37(1). 3–15. 4 indexed citations
10.
Scheffer, Gert‐Jan, Lucas van Eijk, Ignacio Malagon, et al.. (2021). The neuromuscular and multisystem features of RYR1-related malignant hyperthermia and rhabdomyolysis. Medicine. 100(33). e26999–e26999. 7 indexed citations
11.
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
12.
Cameron, Ian, Nens van Alfen, Ivan Toni, et al.. (2020). Altered sensorimotor representations after recovery from peripheral nerve damage in neuralgic amyotrophy. Cortex. 127. 180–190. 9 indexed citations
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15.
Alfen, Nens van. (2017). Editorial on "Ultrasonography in neuralgic amyotrophy: sensitivity, spectrum of findings, and clinical correlations", by Arányi et al.. Muscle & Nerve. 2 indexed citations
16.
Radema, Sandra A., et al.. (2017). Intravenous Lidocaine: Old-School Drug, New Purpose—Reduction of Intractable Pain in Patients with Chemotherapy Induced Peripheral Neuropathy. Pain Research and Management. 2017. 1–9. 33 indexed citations
17.
Goselink, Rianne J.M., Tim H.A. Schreuder, Karlien Mul, et al.. (2016). Facioscapulohumeral dystrophy in children: design of a prospective, observational study on natural history, predictors and clinical impact (iFocus FSHD). BMC Neurology. 16(1). 138–138. 15 indexed citations
18.
Leeuwen-Segarceanu, Elena M. van, Lucille D.A. Dorresteijn, Sigrid Pillen, et al.. (2011). Progressive Muscle Atrophy and Weakness After Treatment by Mantle Field Radiotherapy in Hodgkin Lymphoma Survivors. International Journal of Radiation Oncology*Biology*Physics. 82(2). 612–618. 33 indexed citations
19.
Alfen, Nens van, Richard J. Sinke, Anneke Gabreëls-Festen, et al.. (2001). Intermediate CAG repeat lengths (53,54) for MJD/SCA3 are associated with an abnormal phenotype. Annals of Neurology. 49(6). 805–808. 70 indexed citations
20.
Jonghe, Peter De, Johan A. K. Suykens, A.A.W.M. Gabreëls‐Festen, et al.. (2000). The natural history of hereditary neuralgic amyotrophy in the Dutch population.. Neuromuscular Disorders. 10. 518–524. 3 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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