For: | Wang L, Long DY. Significant risk factors for intensive care unit-acquired weakness: A processing strategy based on repeated machine learning. World J Clin Cases 2024; 12(7): 1235-1242 [PMID: 38524515 DOI: 10.12998/wjcc.v12.i7.1235] |
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URL: | https://www.wjgnet.com/2307-8960/full/v12/i7/1235.htm |
Number | Citing Articles |
1 |
Chinmaya K Panda, Habib Md R Karim. Deep Machine Learning Might Aid in Combating Intensive Care Unit-Acquired Weakness. Cureus 2024; doi: 10.7759/cureus.58963
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2 |
Thirugnanasambandan Sunder. Intensive care unit-acquired weakness – preventive, and therapeutic aspects; future directions and special focus on lung transplantation. World Journal of Clinical Cases 2024; 12(19): 3665-3670 doi: 10.12998/wjcc.v12.i19.3665
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3 |
Jiajiao Liu, Zhaoxia Xu, Shuhong Luo, Yujie Bai, Jian Feng, Fuxiang Li. Risk factors for ICU-acquired weakness in sepsis patients: A retrospective study of 264 patients. Heliyon 2024; 10(11): e32253 doi: 10.1016/j.heliyon.2024.e32253
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4 |
Carlos Martin Ardila, Daniel González-Arroyave, Mateo Zuluaga-Gómez. Predicting intensive care unit-acquired weakness: A multilayer perceptron neural network approach. World Journal of Clinical Cases 2024; 12(12): 2023-2030 doi: 10.12998/wjcc.v12.i12.2023
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5 |
Muad Abdi Hassan, Abdulqadir J Nashwan. Machine learning insights on intensive care unit-acquired weakness. World Journal of Clinical Cases 2024; 12(18): 3285-3287 doi: 10.12998/wjcc.v12.i18.3285
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6 |
Ming Liu, Yu-Tong Chen, Guang-Liang Wang, Xue-Mei Wu. Risk factors for intensive-care-unit-acquired weakness. World Journal of Clinical Cases 2024; 12(21): 4853-4855 doi: 10.12998/wjcc.v12.i21.4853
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7 |
Xiao-Yu He, Yi-Huan Zhao, Qian-Wen Wan, Fu-Shan Tang. Intensive care unit-acquired weakness: Unveiling significant risk factors and preemptive strategies through machine learning. World Journal of Clinical Cases 2024; 12(35): 6760-6763 doi: 10.12998/wjcc.v12.i35.6760
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8 |
Ranjeet Kumar Sinha, Sony Sinha, Prateek Nishant, Arvind Kumar Morya. Intensive care unit-acquired weakness and mechanical ventilation: A reciprocal relationship. World Journal of Clinical Cases 2024; 12(18): 3644-3647 doi: 10.12998/wjcc.v12.i18.3644
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9 |
Georges Khattar, Elie Bou Sanayeh. Advancing critical care recovery: The pivotal role of machine learning in early detection of intensive care unit-acquired weakness. World Journal of Clinical Cases 2024; 12(21): 4455-4459 doi: 10.12998/wjcc.v12.i21.4455
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10 |
Silvano Dragonieri. Pioneering role of machine learning in unveiling intensive care unit-acquired weakness. World Journal of Clinical Cases 2024; 12(13): 2157-2159 doi: 10.12998/wjcc.v12.i13.2157
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11 |
Chun-Yao Cheng, Wen-Rui Hao, Tzu-Hurng Cheng. Unveiling significant risk factors for intensive care unit-acquired weakness: Advancing preventive care. World Journal of Clinical Cases 2024; 12(18): 3288-3290 doi: 10.12998/wjcc.v12.i18.3288
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12 |
Melda Kangalgil, Hülya Ulusoy, Sekine Ayaz. Acute Skeletal Muscle Wasting is Associated with Prolonged Hospital Stay in Critical Illness with Brain Injury. Neurocritical Care 2024; doi: 10.1007/s12028-024-02017-y
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