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Journal Abstract Search

353 related items for PubMed ID: 39118122

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  • 5. Using machine learning to identify patients at high risk of developing low bone density or osteoporosis after gastrectomy: a 10-year multicenter retrospective analysis.
    Zhu Y, Liu Y, Wang Q, Niu S, Wang L, Cheng C, Chen X, Liu J, Zhao S.
    J Cancer Res Clin Oncol; 2023 Dec; 149(19):17479-17493. PubMed ID: 37897658
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  • 6. Develop a radiomics-based machine learning model to predict the stone-free rate post-percutaneous nephrolithotomy.
    Zou XC, Luo CW, Yuan RM, Jin MN, Zeng T, Chao HC.
    Urolithiasis; 2024 Apr 13; 52(1):64. PubMed ID: 38613668
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  • 7. Ten-Year Multicenter Retrospective Study Utilizing Machine Learning Algorithms to Identify Patients at High Risk of Venous Thromboembolism After Radical Gastrectomy.
    Liu Y, Song C, Tian Z, Shen W.
    Int J Gen Med; 2023 Apr 13; 16():1909-1925. PubMed ID: 37228741
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  • 8. Can Predictive Modeling Tools Identify Patients at High Risk of Prolonged Opioid Use After ACL Reconstruction?
    Anderson AB, Grazal CF, Balazs GC, Potter BK, Dickens JF, Forsberg JA.
    Clin Orthop Relat Res; 2020 Jul 13; 478(7):0-1618. PubMed ID: 32282466
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  • 9. [Construction of a predictive model for in-hospital mortality of sepsis patients in intensive care unit based on machine learning].
    Zhu M, Hu C, He Y, Qian Y, Tang S, Hu Q, Hao C.
    Zhonghua Wei Zhong Bing Ji Jiu Yi Xue; 2023 Jul 13; 35(7):696-701. PubMed ID: 37545445
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  • 12. Prediction of Acute Kidney Injury after Extracorporeal Cardiac Surgery (CSA-AKI) by Machine Learning Algorithms.
    Tong Y, Niu X, Liu F.
    Heart Surg Forum; 2023 Oct 25; 26(5):E537-E551. PubMed ID: 37920093
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  • 13. Establishment and validation of a heart failure risk prediction model for elderly patients after coronary rotational atherectomy based on machine learning.
    Zhang L, Zhou X, Cao J.
    PeerJ; 2024 Oct 25; 12():e16867. PubMed ID: 38313005
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  • 16. Prediction of postoperative infectious complications in elderly patients with colorectal cancer: a study based on improved machine learning.
    Tian Y, Li R, Wang G, Xu K, Li H, He L.
    BMC Med Inform Decis Mak; 2024 Jan 06; 24(1):11. PubMed ID: 38184556
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  • 17. Predictive model and risk analysis for peripheral vascular disease in type 2 diabetes mellitus patients using machine learning and shapley additive explanation.
    Liu L, Bi B, Cao L, Gui M, Ju F.
    Front Endocrinol (Lausanne); 2024 Jan 06; 15():1320335. PubMed ID: 38481447
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  • 18. Predictive etiological classification of acute ischemic stroke through interpretable machine learning algorithms: a multicenter, prospective cohort study.
    Chen S, Yang X, Gu H, Wang Y, Xu Z, Jiang Y, Wang Y.
    BMC Med Res Methodol; 2024 Sep 10; 24(1):199. PubMed ID: 39256656
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