Risk stratification by nomogram of deep learning radiomics based on multiparametric magnetic resonance imaging in knee meniscus injury
Author:
Publisher
Springer Science and Business Media LLC
Subject
Orthopedics and Sports Medicine,Surgery
Link
https://link.springer.com/content/pdf/10.1007/s00264-023-05875-x.pdf
Reference26 articles.
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2. Fox AJ, Wanivenhaus F, Burge AJ, Warren RF, Rodeo SA (2015) The human meniscus: a review of anatomy, function, injury, and advances in treatment. Clin Anat 28(2):269–287. https://doi.org/10.1002/ca.22456
3. Kawahara T, Sasho T, Katsuragi J, Ohnishi T, Haneishi H (2017) Relationship between knee osteoarthritis and meniscal shape in observation of Japanese patients by using magnetic resonance imaging. J Orthop Surg Res 12(1):97. https://doi.org/10.1186/s13018-017-0595-y
4. Malanga GA, Chirichella PS, Hogaboom NS, Capella T (2021) Clinical evaluation of micro-fragmented adipose tissue as a treatment option for patients with meniscus tears with osteoarthritis: a prospective pilot study. Int Orthop 45(2):473–480. https://doi.org/10.1007/s00264-020-04835-z
5. Bien N, Rajpurkar P, Ball RL, Irvin J, Park A, Jones E, Bereket M, Patel BN, Yeom KW, Shpanskaya K, Halabi S, Zucker E, Fanton G, Amanatullah DF, Beaulieu CF, Riley GM, Stewart RJ, Blankenberg FG, Larson DB et al (2018) Deep-learning-assisted diagnosis for knee magnetic resonance imaging: development and retrospective validation of MRNet. Plos Med 15(11):e1002699. https://doi.org/10.1371/journal.pmed.1002699
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