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Journal Abstract Search

465 related items for PubMed ID: 38380369

  • 41. Interpretable machine learning model for early prediction of delirium in elderly patients following intensive care unit admission: a derivation and validation study.
    Tang D, Ma C, Xu Y.
    Front Med (Lausanne); 2024; 11():1399848. PubMed ID: 38828233
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  • 42. Machine learning-based models for the prediction of breast cancer recurrence risk.
    Zuo D, Yang L, Jin Y, Qi H, Liu Y, Ren L.
    BMC Med Inform Decis Mak; 2023 Nov 29; 23(1):276. PubMed ID: 38031071
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  • 44. Machine learning-enabled prediction of prolonged length of stay in hospital after surgery for tuberculosis spondylitis patients with unbalanced data: a novel approach using explainable artificial intelligence (XAI).
    Yasin P, Yimit Y, Cai X, Aimaiti A, Sheng W, Mamat M, Nijiati M.
    Eur J Med Res; 2024 Jul 25; 29(1):383. PubMed ID: 39054495
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  • 45. Predicting sepsis in-hospital mortality with machine learning: a multi-center study using clinical and inflammatory biomarkers.
    Zhang G, Shao F, Yuan W, Wu J, Qi X, Gao J, Shao R, Tang Z, Wang T.
    Eur J Med Res; 2024 Mar 06; 29(1):156. PubMed ID: 38448999
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  • 46. Development and validation of artificial intelligence models for preoperative prediction of inferior mesenteric artery lymph nodes metastasis in left colon and rectal cancer.
    Wang X, Zheng Z, Xie Z, Yu Q, Lu X, Zhao Z, Huang S, Huang Y, Chi P.
    Eur J Surg Oncol; 2022 Dec 06; 48(12):2475-2486. PubMed ID: 35864013
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  • 53. A 5-year survival status prognosis of nonmetastatic cervical cancer patients through machine learning algorithms.
    Yu W, Lu Y, Shou H, Xu H, Shi L, Geng X, Song T.
    Cancer Med; 2023 Mar 06; 12(6):6867-6876. PubMed ID: 36479910
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  • 54. Machine Learning-Based Prediction of Acute Kidney Injury Following Pediatric Cardiac Surgery: Model Development and Validation Study.
    Luo XQ, Kang YX, Duan SB, Yan P, Song GB, Zhang NY, Yang SK, Li JX, Zhang H.
    J Med Internet Res; 2023 Jan 05; 25():e41142. PubMed ID: 36603200
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  • 58. Artificial intelligence based system for predicting permanent stoma after sphincter saving operations.
    Kuo CY, Kuo LJ, Lin YK.
    Sci Rep; 2023 Sep 25; 13(1):16039. PubMed ID: 37749194
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  • 59. Multiparametric magnetic resonance imaging (MRI)-based radiomics model explained by the Shapley Additive exPlanations (SHAP) method for predicting complete response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer: a multicenter retrospective study.
    Wang Y, Zhang L, Jiang Y, Cheng X, He W, Yu H, Li X, Yang J, Yao G, Lu Z, Zhang Y, Yan S, Zhao F.
    Quant Imaging Med Surg; 2024 Jul 01; 14(7):4617-4634. PubMed ID: 39022292
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  • 60. Machine learning based prediction of recurrence after curative resection for rectal cancer.
    Jeon Y, Kim YJ, Jeon J, Nam KH, Hwang TS, Kim KG, Baek JH.
    PLoS One; 2023 Jul 01; 18(12):e0290141. PubMed ID: 38100485
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