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[Development of a machine learning-based model for assessing pulmonary function in elderly patients]. [PDF]

Nan Fang Yi Ke Da Xue Xue Bao
Chen C, Zhang W, Cai Y, Ouyang M, Liang Y, Liang M, Liang H.   +6 more
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[Interpretation of 2025 American Academy of Orthopaedic Surgeons (AAOS) on Management of Acute Compartment Syndrome Evidence-Based Clinical Practice Guideline]. [PDF]

Zhongguo Xiu Fu Chong Jian Wai Ke Za Zhi
Ye Y, Lu B, Xiao C, Lan F, Li X, Zhang K.   +5 more
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[Etiology, Evaluation and Comprehensive Management of Hoarseness 
after Lung Cancer Surgery]. [PDF]

Zhongguo Fei Ai Za Zhi
Men P, Liang J, Zhang F, Wang X.
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[Expectant management versus acetaminophen for early treatment of hemodynamically significant patent ductus arteriosus in very preterm infants: a randomized controlled trial]. [PDF]

Zhongguo Dang Dai Er Ke Za Zhi
Xu SY, Wang BJ, Li Z, Yang KD, Wang LY, Xu N, Wang ZX, Li M, Gao XY.   +8 more
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[Effects of <i>Baduanjin</i>, bedside cycle ergometer and balloon-blowing training on pulmonary function recovery following thoracoscopic surgery for lung cancer: a randomized controlled trial]. [PDF]

Nan Fang Yi Ke Da Xue Xue Bao
Zhang J, Yao S, Zhao Z, Sun X, Zhu Z, Li L, Wei H.   +6 more
europepmc   +1 more source

[Advanced Enteric-type Thymic Adenocarcinoma with Axillary Lymph Node 
Oligometastasis: A Case Report]. [PDF]

Zhongguo Fei Ai Za Zhi
Huang C, Wang Z, Tong H.
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[Association between adverse outcomes during hospitalization and early postnatal weight changes in term appropriate-for-gestational-age infants with early-onset sepsis]. [PDF]

Zhongguo Dang Dai Er Ke Za Zhi
Zeng SC, Zhou XL, Xiang LL, Hua ZY.
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[Clinical characteristics and outcomes of neonatal dengue fever in Foshan]. [PDF]

Zhongguo Dang Dai Er Ke Za Zhi
Luo FJ, Dai YH, Chen J, Yuan GL, Mo WH, Xu QQ, Jie WQ, Guo WZ, Deng ZQ, Li LS, Shi JP.   +10 more
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[Dynamic changes and physiological regulation of common carotid artery blood flow during general anesthesia in elderly patients: a prospective study]. [PDF]

Nan Fang Yi Ke Da Xue Xue Bao
Liu X, Wu J, Ye C, Wang E, Hu H.
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基于人工智能的空气压缩机故障树分析研究

科学技术与教育
本文开展基于人工智能的空气压缩机故障树分析方法研究,旨在提升设备故障诊断的精准度与检测效率。空气压缩机作为工业生产中的核心关键设备,运行过程中一旦出现故障,不仅会造成生产流程停滞,还严重影响工业生产安全与整体运行效率,因此引入先进智能故障诊断技术具有重要工程应用价值。本文将人工智能技术与故障树分析法相融合,构建空气压缩机智能故障分析模型。研究表明,二者有机结合可有效提升故障诊断的智能化、自动化水平,能够快速定位故障诱因,为工业空气压缩机设备的日常运维、故障排查及精细化管理提供科学依据与可靠技术支撑。
Liang Zhao
semanticscholar   +1 more source