BPG is committed to discovery and dissemination of knowledge
Cited by in CrossRef
For: Xu SM, Dong D, Li W, Bai T, Zhu MZ, Gu GS. Deep learning-assisted diagnosis of femoral trochlear dysplasia based on magnetic resonance imaging measurements. World J Clin Cases 2023; 11(7): 1477-1487 [PMID: 36926411 DOI: 10.12998/wjcc.v11.i7.1477]
URL: https://www.wjgnet.com/2307-8960/full/v11/i7/1477.htm
Number Citing Articles
1
Immunomodulatory effects and mechanisms of the extracts and secondary compounds of Zingiber and Alpinia species: a reviewFrontiers in Pharmacology 2023; 14 doi: 10.3389/fphar.2023.1222195
2
Jack Twomey-Kozak, Mikhail A. Bethell, Zoe Wiatt Hinton, Samuel Lorentz, Lucy Meyer, Alex Meyer, Eoghan Hurley, Damon V. Briggs, Kendall Bradley, Jocelyn Wittstein, Brian Lau. Artificial Intelligence Has Varied Diagnostic and Predictive Performance in Diagnosing Patellofemoral Osteoarthritis, Trochlear Dysplasia and Patellofemoral Tracking: A Systematic ReviewArthroscopy, Sports Medicine, and Rehabilitation 2025; : 101269 doi: 10.1016/j.asmr.2025.101269
3
David H. Dejour, Edoardo Giovanetti de Sanctis, Jacobus H. Müller, Etienne Deroche, Tomas Pineda, Amedeo Guarino, Cécile Toanen. Adapting the Dejour classification of trochlear dysplasia from qualitative radiograph‐ and CT‐based assessments to quantitative MRI‐based measurementsKnee Surgery, Sports Traumatology, Arthroscopy 2025; 33(8): 2833 doi: 10.1002/ksa.12539
4
Hongwei Zhan, Zandong Zhao, Qiuzhen Liang, Jiang Zheng, Liang Zhang. Performance of artificial intelligence in automated measurement of patellofemoral joint parameters: a systematic reviewJournal of Orthopaedic Surgery and Research 2025; 20(1) doi: 10.1186/s13018-025-06247-4