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Cited by in CrossRef
For: Tian CW, Chen XX, Shi L, Zhu HY, Dai GC, Chen H, Rui YF. Machine learning applications for the prediction of extended length of stay in geriatric hip fracture patients. World J Orthop 2023; 14(10): 741-754 [PMID: 37970626 DOI: 10.5312/wjo.v14.i10.741]
URL: https://www.wjgnet.com/2218-5836/full/v14/i10/741.htm
Number Citing Articles
1
Hao Liu, Fei Xing, Jiabao Jiang, Zhao Chen, Zhou Xiang, Xin Duan. Random forest predictive modeling of prolonged hospital length of stay in elderly hip fracture patientsFrontiers in Medicine 2024; 11 doi: 10.3389/fmed.2024.1362153
2
Chuwei Tian, Yucheng Gao, Chen Rui, Shengbo Qin, Liu Shi, Yunfeng Rui. Artificial intelligence in orthopaedic traumaEngMedicine 2024; 1(2): 100020 doi: 10.1016/j.engmed.2024.100020
3
Christel Sirocchi, Alessandro Bogliolo, Sara Montagna. Medical-informed machine learning: integrating prior knowledge into medical decision systemsBMC Medical Informatics and Decision Making 2024; 24(S4) doi: 10.1186/s12911-024-02582-4
4
Andrea Campagner, Frida Milella, Giuseppe Banfi, Federico Cabitza. Second opinion machine learning for fast-track pathway assignment in hip and knee replacement surgery: the use of patient-reported outcome measuresBMC Medical Informatics and Decision Making 2024; 24(S4) doi: 10.1186/s12911-024-02602-3
5
Miaotian Tang, Meng Zhang, Yu Dang, Mingxing Lei, Dianying Zhang. Machine Learning-Based Prediction of Postoperative Pneumonia Among Super-Aged Patients With Hip FractureClinical Interventions in Aging 2025; : 217 doi: 10.2147/CIA.S507138