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Mar 6, 2024 (publication date) through May 18, 2024

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World Journal of Clinical Cases

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2307-8960

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Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA

Cited by in CrossRef

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]
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
2	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 Abstract(97) \| Core Tip(59) \| Full Article(HTML)(443) \| Full Article with Cover (PDF)-2020K(9) \| Audio-480K(3) \| Peer-Review Report-215K(6) \| Answering Reviewers-29K(6) \| Full Article (PDF)-484K(23) \| Full Article (XML)-69K(8) \| Times Cited (0) \| Total Visits (1036) \| Open
3	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 Abstract(91) \| Core Tip(74) \| Full Article(HTML)(215) \| Full Article with Cover (PDF)-585K(10) \| Audio-306K(0) \| Peer-Review Report-214K(7) \| Answering Reviewers-215K(8) \| Full Article (PDF)-314K(12) \| Full Article (XML)-13K(6) \| Times Cited (0) \| Total Visits (536) \| Open