Hans Van Eetvelde

411 citations
4 papers · 215 · 1 hit paper · h-index 4

Impact in

Papers in

Hans Van Eetvelde

4 papers receiving 209 citations

Hans Van Eetvelde's Hit Papers

Machine learning methods in sport injury prediction and prevention: a systematic review 2021 · 169 citations
1690+1+3Years since publication50100150

Peers

Hans Van Eetvelde
Comparison fields: 5 of 51
  • Orthopedics and Sports Medicine 105
  • Health Informatics 11
  • Economics and Econometrics 61
  • Physical Therapy, Sports Therapy and Rehabilitation 5
  • Cardiology and Cardiovascular Medicine 23
Replace Tom Hughes with:
Tom Hughes United Kingdom
Vangelis Sarlis Greece
Floris Goes Netherlands
Jo Clubb United Kingdom
Daniel Linke Germany
Carlo Dindorf Germany
Mindaugas Balčiūnas Lithuania
John J. Orriola United States
Norma Coffey Ireland
Walter R. Smith United States
Hans Van Eetvelde relative to Tom Hughes United Kingdom Tom Hughes's profile →
Citations per field
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Citations per year

Countries citing papers authored by Hans Van Eetvelde

Since Specialization
Citations

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

Fields of papers citing papers by Hans Van Eetvelde

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hans Van Eetvelde. 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 Hans Van Eetvelde. The network helps show where Hans Van Eetvelde may publish in the future.

Co-authors

The 9 scholars most cited alongside Hans Van Eetvelde, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Hans Van Eetvelde Line = papers co-authored together Hans Van Eetvelde links everyone, so they are left out of the graph.

All Works

4 of 4 papers shown
#Work
1
Machine learning methods in sport injury prediction and prevention: a systematic review
Hit paper breakdown →
2021169
2 201935
3 20217
4 20214

About Hans Van Eetvelde

Hans Van Eetvelde is a scholar working on Economics and Econometrics, Orthopedics and Sports Medicine, Nature and Landscape Conservation, Computer Vision and Pattern Recognition and Signal Processing, having authored 4 papers that have together received 215 indexed citations. Recurring topics across this work include Sports Analytics and Performance (3 papers), Sports Performance and Training (2 papers), Time Series Analysis and Forecasting (1 paper), Data Visualization and Analytics (1 paper), Sports Dynamics and Biomechanics (1 paper) and Forest ecology and management (1 paper). The work is most often cited by research in Orthopedics and Sports Medicine (105 citations), Health Informatics (11 citations), Economics and Econometrics (61 citations), Physical Therapy, Sports Therapy and Rehabilitation (5 citations) and Cardiology and Cardiovascular Medicine (23 citations). Hans Van Eetvelde has collaborated with scholars based in Belgium, Germany and Norway. Frequent co-authors include Christophe Ley, Luciana De Michelis Mendonça, Thomas Tischer, Romain Seil, Andreas Groll, Gunther Schauberger, Lars Magnus Hvattum, Ulf Brefeld and Claus Thorn Ekstrøm. Their work appears in journals such as Journal of Quantitative Analysis in Sports, Journal of Experimental Orthopaedics, Multilingual Matters (Channel View Publications) and RePEc: Research Papers in Economics.

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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