Grand challenge competition to predict in vivo knee loads
Impact in
- Surgery 281
Classified as
- Journal
- Journal of Orthopaedic Research®
In The Last Decade
doi.org/10.1002/jor.22023 →Countries where authors are citing Grand challenge competition to predict in vivo knee loads
This map shows the geographic impact of Grand challenge competition to predict in vivo knee loads. 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 Grand challenge competition to predict in vivo knee loads with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Grand challenge competition to predict in vivo knee loads more than expected).
Fields of papers citing Grand challenge competition to predict in vivo knee loads
This network shows the impact of Grand challenge competition to predict in vivo knee loads. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Grand challenge competition to predict in vivo knee loads.
About Grand challenge competition to predict in vivo knee loads
This paper, published in 2011, received 494 indexed citations . Written by Benjamin Jon Fregly, Thor F. Besier, David G. Lloyd, Scott L. Delp, Scott Arthur Banks, Marcus G. Pandy and Darryl D. DʼLima covering the research area of Biomedical Engineering and Surgery. It is primarily cited by scholars working on Biomedical Engineering (296 citations), Surgery (281 citations), Orthopedics and Sports Medicine (66 citations), Rheumatology (47 citations) and Cognitive Neuroscience (35 citations). Published in Journal of Orthopaedic Research®.
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.
This paper is also available at doi.org/10.1002/jor.22023.