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For: Lalehzarian SP, Gowd AK, Liu JN. Machine learning in orthopaedic surgery. World J Orthop 2021; 12(9): 685-699 [PMID: 34631452 DOI: 10.5312/wjo.v12.i9.685]
URL: https://www.wjgnet.com/1948-5182/full/v12/i9/685.htm
Number Citing Articles
1
Hua Wang, Jichong Ying, Jianlei Liu, Tianming Yu, Dichao Huang. Harnessing ResNet50 and SENet for enhanced ankle fracture identificationBMC Musculoskeletal Disorders 2024; 25(1) doi: 10.1186/s12891-024-07355-8
2
Shuya Tanaka, Atsuyuki Inui, Yutaka Mifune, Hanako Nishimoto, Issei Shinohara, Takahiro Furukawa, Tatsuo Kato, Masaya Kusunose, Yutaka Ehara, Shunsaku Takigami, Ryosuke Kuroda. Dynamic Analysis of the Median Nerve in Carpal Tunnel Syndrome from Ultrasound Images Using the YOLOv5 Object Detection ModelApplied Sciences 2023; 13(24): 13256 doi: 10.3390/app132413256
3
Jeremy A. Dubin, Sandeep S. Bains, Zhongming Chen, Daniel Hameed, James Nace, Michael A. Mont, Ronald E. Delanois. Using a Google Web Search Analysis to Assess the Utility of ChatGPT in Total Joint ArthroplastyThe Journal of Arthroplasty 2023; 38(7): 1195 doi: 10.1016/j.arth.2023.04.007
4
Taylor P. Stauffer, Billy I. Kim, Caitlin Grant, Samuel B. Adams, Albert T. Anastasio. Robotic Technology in Foot and Ankle Surgery: A Comprehensive ReviewSensors 2023; 23(2): 686 doi: 10.3390/s23020686
5
Dirk Stengel, Johannes Wünscher, Luzi Dubs, Axel Ekkernkamp, Tobias Renkawitz. Evidenzbasierte Medizin versus Erfahrungsmedizin in Orthopädie und UnfallchirurgieDie Orthopädie 2023; 52(6): 435 doi: 10.1007/s00132-023-04382-6
6
Issei Shinohara, Atsuyuki Inui, Yutaka Mifune, Hanako Nishimoto, Kohei Yamaura, Shintaro Mukohara, Tomoya Yoshikawa, Tatsuo Kato, Takahiro Furukawa, Yuichi Hoshino, Takehiko Matsushita, Ryosuke Kuroda. Diagnosis of Cubital Tunnel Syndrome Using Deep Learning on Ultrasonographic ImagesDiagnostics 2022; 12(3): 632 doi: 10.3390/diagnostics12030632
7
Xiaowen Zhou, Hua Wang, Chengyao Feng, Ruilin Xu, Yu He, Lan Li, Chao Tu. Emerging Applications of Deep Learning in Bone Tumors: Current Advances and ChallengesFrontiers in Oncology 2022; 12 doi: 10.3389/fonc.2022.908873
8
Chu-Wei Tian, Xiang-Xu Chen, Liu Shi, Huan-Yi Zhu, Guang-Chun Dai, Hui Chen, Yun-Feng Rui. Machine learning applications for the prediction of extended length of stay in geriatric hip fracture patientsWorld Journal of Orthopedics 2023; 14(10): 741-754 doi: 10.5312/wjo.v14.i10.741
9
Edoardo Franceschetti, Pietro Gregori, Simone De Giorgi, Tommaso Martire, Pierangelo Za, Giuseppe Francesco Papalia, Giancarlo Giurazza, Umile Giuseppe Longo, Rocco Papalia. Machine learning can predict anterior elevation after reverse total shoulder arthroplasty: A new tool for daily outpatient clinic?MUSCULOSKELETAL SURGERY 2024;  doi: 10.1007/s12306-023-00811-z
10
Ray Marks. Artificial Intelligence and Its Potential Application in Advancing Hip Osteoarthritis CareJournal of Orthopaedic Science and Research 2023; : 1 doi: 10.46889/JOSR.2023.4207
11
Fatemeh Arjmandnia, Ehsan Alimohammadi. The value of machine learning technology and artificial intelligence to enhance patient safety in spine surgery: a reviewPatient Safety in Surgery 2024; 18(1) doi: 10.1186/s13037-024-00393-0
12
Michael A. Kurtz, Ruoyu Yang, Mohan S.R. Elapolu, Audrey C. Wessinger, William Nelson, Kazzandra Alaniz, Rahul Rai, Jeremy L. Gilbert. Predicting Corrosion Damage in the Human Body Using Artificial IntelligenceOrthopedic Clinics of North America 2023; 54(2): 169 doi: 10.1016/j.ocl.2022.11.004
13
Mitsumasa Hida, Shinji Eto, Chikamune Wada, Kodai Kitagawa, Masakazu Imaoka, Misa Nakamura, Ryota Imai, Takanari Kubo, Takao Inoue, Keiko Sakai, Junya Orui, Fumie Tazaki, Masatoshi Takeda, Ayuna Hasegawa, Kota Yamasaka, Hidetoshi Nakao. Development of Hallux Valgus Classification Using Digital Foot Images with Machine LearningLife 2023; 13(5): 1146 doi: 10.3390/life13051146
14
Madhan Jeyaraman, Arulkumar Nallakumarasamy, Naveen Jeyaraman. Industry 5.0 in OrthopaedicsIndian Journal of Orthopaedics 2022; 56(10): 1694 doi: 10.1007/s43465-022-00712-6
15
Julie M. Parrott, Austen J. Parrott, Armaun D. Rouhi, J. Scott Parrott, Kristoffel R. Dumon. What We Are Missing: Using Machine Learning Models to Predict Vitamin C Deficiency in Patients with Metabolic and Bariatric SurgeryObesity Surgery 2023; 33(6): 1710 doi: 10.1007/s11695-023-06571-w
16
Oleg Titov, Andrey Bykanov, David Pitskhelauri. Neurosurgical skills analysis by machine learning models: systematic reviewNeurosurgical Review 2023; 46(1) doi: 10.1007/s10143-023-02028-x
17
Konrad Kwolek, Artur Gądek, Kamil Kwolek, Radek Kolecki, Henryk Liszka. Automated decision support for Hallux Valgus treatment options using anteroposterior foot radiographsWorld Journal of Orthopedics 2023; 14(11): 800-812 doi: 10.5312/wjo.v14.i11.800
18
Aakash K. Shah, Monish S. Lavu, Christian J. Hecht, Robert J. Burkhart, Atul F. Kamath. Understanding the use of artificial intelligence for implant analysis in total joint arthroplasty: a systematic reviewArthroplasty 2023; 5(1) doi: 10.1186/s42836-023-00209-z
19
Aamir Amin, Swizel Ann Cardoso, Jenisha Suyambu, Hafiz Abdus Saboor, Rayner P Cardoso, Ali Husnain, Natasha Varghese Isaac, Haydee Backing, Dalia Mehmood, Maria Mehmood, Abdalkareem Nael Jameel Maslamani. Future of Artificial Intelligence in Surgery: A Narrative ReviewCureus 2024;  doi: 10.7759/cureus.51631
20
Taekyeong Kim, Tae Sik Goh, Jung Sub Lee, Ji Hyun Lee, Hayeol Kim, Im Doo Jung. Transfer learning-based ensemble convolutional neural network for accelerated diagnosis of foot fracturesPhysical and Engineering Sciences in Medicine 2023; 46(1): 265 doi: 10.1007/s13246-023-01215-w
21
Jun Ho Chung, Damien Cannon, Matthew Gulbrandsen, Dheeraj Yalamanchili, Wesley P. Phipatanakul, Joseph Liu, Anirudh Gowd, Anthony Essilfie. Random forest identifies predictors of discharge destination following total shoulder arthroplastyJSES International 2024; 8(2): 317 doi: 10.1016/j.jseint.2023.04.003
22
Man-Soo Kim, Ryu-Kyoung Cho, Sung-Cheol Yang, Jae-Hyeong Hur, Yong In. Machine Learning for Detecting Total Knee Arthroplasty Implant Loosening on Plain RadiographsBioengineering 2023; 10(6): 632 doi: 10.3390/bioengineering10060632
23
Karthikeyan P. Iyengar, Eindere Zaw Pe, Janaranjan Jalli, Madapura K. Shashidhara, Vijay K. Jain, Abhishek Vaish, Raju Vaishya. Industry 5.0 technology capabilities in Trauma and OrthopaedicsJournal of Orthopaedics 2022; 32: 125 doi: 10.1016/j.jor.2022.06.001
24
Madhan Jeyaraman, Harish V K Ratna, Naveen Jeyaraman, Aakaash Venkatesan, Swaminathan Ramasubramanian , Sankalp Yadav. Leveraging Artificial Intelligence and Machine Learning in Regenerative Orthopedics: A Paradigm Shift in Patient CareCureus 2023;  doi: 10.7759/cureus.49756
25
Albert T. Anastasio, Bailey S. Zinger, Thomas J. Anastasio, Kathiravan Srinivasan. A novel application of neural networks to identify potentially effective combinations of biologic factors for enhancement of bone fusion/repairPLOS ONE 2022; 17(11): e0276562 doi: 10.1371/journal.pone.0276562
26
Sheridan Perry, Matthew Folkman, Takara O'Brien, Lauren A. Wilson, Eric Coyle, Raymond W. Liu, Charles T. Price, Victor A. Huayamave. Unaligned Hip Radiograph Assessment Utilizing Convolutional Neural Networks for the Assessment of Developmental Dysplasia of the HipJournal of Engineering and Science in Medical Diagnostics and Therapy 2024; 7(4) doi: 10.1115/1.4064988
27
Marie K. Reumann, Benedikt J. Braun, Maximilian M. Menger, Fabian Springer, Johann Jazewitsch, Tobias Schwarz, Andreas Nüssler, Tina Histing, Mika F. R. Rollmann. Künstliche Intelligenz und Ausblick auf Anwendungsfelder in der PseudarthrosentherapieDie Unfallchirurgie 2022; 125(8): 611 doi: 10.1007/s00113-022-01202-y
28
Yi-Chao Wu, Chao-Yun Chang, Yu-Tse Huang, Sung-Yuan Chen, Cheng-Hsuan Chen, Hsuan-Kai Kao. Artificial Intelligence Image Recognition System for Preventing Wrong-Site Upper Limb SurgeryDiagnostics 2023; 13(24): 3667 doi: 10.3390/diagnostics13243667
29
S Santhiya, N Abinaya, P Jayadharshini, S Priyanka, S Keerthika, C Sharmila. Orthopedic patient analysis using machine learning techniquesJournal of Physics: Conference Series 2023; 2664(1): 012004 doi: 10.1088/1742-6596/2664/1/012004
30
Anirudh K. Gowd, Conor N. O’Neill, Ameen Barghi, Tadhg J. O’Gara, Jonathan J. Carmouche. Feasibility of Machine Learning in the Prediction of Short-Term Outcomes Following Anterior Cervical Discectomy and FusionWorld Neurosurgery 2022; 168: e223 doi: 10.1016/j.wneu.2022.09.090
31
Srinivasan Sridhar, Bradley Whitaker, Amy Mouat-Hunter, Bernadette McCrory, Faizan Iqbal. Predicting Length of Stay using machine learning for total joint replacements performed at a rural community hospitalPLOS ONE 2022; 17(11): e0277479 doi: 10.1371/journal.pone.0277479
32
Artificial Intelligence and Machine Learning in Prediction of Total Hip Arthroplasty Outcome: A Bibliographic ReviewE3S Web of Conferences 2023; 448: 02054 doi: 10.1051/e3sconf/202344802054