Deep learning-based ranking method for subgroup and predictive biomarker identification in patients by Zihuan Liu, Yihua Gu, Xin Huang

“…Methods We introduce DeepRAB, a deep learning-based framework designed for exploring treatment effect heterogeneity by constructing individualized treatment rule (ITR). …”
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A Deep Learning Method for Automatic Coronal Mass Ejection Feature Identification by P. Yang, H. S. Fu, J. B. Cao, F. Shen

“…Quantitative evaluations demonstrate that the proposed method performs well in metrics such as pixel accuracy, recall, F _1 score, and IoU. …”
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A Fault Diagnosis Method for Wind Turbines Based on Zero-Shot Learning by PAN Meiqi, HE Xing

“…Finally, the effectiveness and superiority of the proposed fault diagnosis method are validated by comparing it with other zero-shot learning methods.…”
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Deep Forest Modeling: An Interpretable Deep Learning Method for Mineral Prospectivity Mapping by Yue‐Lin Dong, Zhen‐Jie Zhang

“…The use of artificial intelligence and big data has advanced mineral prediction into intelligent forecasting. Machine learning methods have shown significant promise in enhancing outcomes. …”
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Research on asynchronous robust federated learning method in vehicle computing power network by YIN Hongbo, WANG Shuai, ZHANG Ke, ZHANG Yin

“…To address the above issues, an asynchronous robust federated learning method was proposed, which achieves vehicle data privacy protection while improving the efficiency of model collaborative training through asynchronous execution of federated learning processes between vehicles. …”
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A deep-learning based method for accelerating dynamic reconfiguration of distribution networks by Yuxuan Wu, Tao Qian, Jingwen Ye, Qinran Hu, Qiangsheng Bu, Zhigang Ye

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A Machine-Learning-Based Classification Method for Meteorological Conditions of Ozone Pollution by Yang Cao, Xiaoli Zhao, Debin Su, Xiang Cheng, Hong Ren

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Automatic Restoration of Dunhuang Murals and Process Visualization Method Based on Deep Learning by Miao Jia, Jie Hu, Zhongliang Yang, Weijie Liu, Jin Qi, Bin Chen

“…This method implements observations of the filling-in process in the defective areas. …”
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An online learning method for assessing smart grid stability under dynamic perturbations by Alaa Alaerjan, Randa Jabeur

“…Through iterative learning cycles augmented by incremental perturbation adjustments, our method significantly improves predictive accuracy. …”
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Methodical aspects of using of Web 2.0 services in the process of blended learning by Diana V. Moglan

“…The problem of finding the optimal combination of forms, methods and means of training is one of the key to providing a holistic learning process.The purpose of this work is to consider the methodological aspects of the organization of blended learning using Web 2.0 services to improve the quality of educational services and motivate students to perform various types of educational activities.The main part of the article considers with the educational opportunities of the most popular Web 2.0 services, the pedagogical features and the nature of the implementation of study assignments in the process of blended learning, identifies the specifics of implementing joint activities in the Internet, and determines the approaches to organizing the network interaction of the teacher and students. …”
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Risk assessment of tunnel water inrush based on Delphi method and machine learning by Leizhi Dong, Qingsong Wang, Weiguo Zhang, Yongjun Zhang, Xiaoshuang Li, Fei Liu

“…To avoid the potential water inrush, this paper proposes a risk assessment model for the metro tunnel based on Delphi survey method and machine learning. The proposed model consists of two parts, the risk assessment index system and the risk level prediction model. …”
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Unsupervised Machine Learning for Effective Code Smell Detection: A Novel Method by Ruchin Gupta, Narendra Kumar, Sunil Kumar, Jitendra Kumar Seth

“…To overcome these challenges, this study introduces a method that leverages unsupervised machine learning (UnML) along with feature engineering. …”
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Pointer meters recognition method in the wild based on innovative deep learning techniques by Jiajun Feng, Haibo Luo, Rui Ming

“…We also combine the output of the decoder network and the output of the improved CBAM as inputs to the Object Heatmap-Scalarmap Module to find pointer tip heat map peaks and predict pointer pointing. The method proposed in this paper is compared with several deep learning networks. …”
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An Automatic Damage Detection Method Based on Adaptive Theory-Assisted Reinforcement Learning by Chengwen Zhang, Qing Chun, Yijie Lin

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Assessing individual genetic susceptibility to metabolic syndrome: interpretable machine learning method by Tao Huang, Yuanyuan Li, Simin Wang, Shijie Qiao, Xiujuan Zheng, Wenhui Xiong, Menghan Yang, Xirui Huang, Bizhen Gao

“…However, there is a lack of machine-learning (ML)-based predictive models to assess individual genetic susceptibility to MetS. …”
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Design of Iterative Learning Control Method with Global Convergence Property for Nonlinear Systems by Guang-Wei Xu, Cheng Shao, Yu Han

“…We address an iterative learning control (ILC) method for overcoming initial value problem caused by local convergence methods. …”
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News Text Classification Method and Simulation Based on the Hybrid Deep Learning Model by Ningfeng Sun, Chengye Du

“…This paper uses the database as the data source, using bibliometrics and visual analysis methods, to statistically analyze the relevant documents published in the field of text classification in the past ten years, to clarify the development context and research status of the text classification field, and to predict the research in the field of text classification priorities and research frontiers. …”
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A Contrastive Representation Learning Method for Event Classification in Φ-OTDR Systems by Tong Zhang, Xinjie Peng, Yifan Liu, Kaiyang Yin, Pengfei Li

“…The experimental results demonstrate that CLWTNet achieves competitive performance with the supervised representation learning methods and superior performance to unsupervised representation learning methods, even when training with unlabeled signal data. …”
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A Quantum Q-Learning Fault Diagnosis Method for Intelligent Manufacturing Equipment by Yi Chen, Kai Deng, Xuelin Du, Zichao Chang, Tong Wan

“…Stringent demands for high-efficiency and high-precision diagnosis are increasingly being unmet by conventional fault diagnosis methods. To address these challenges, a novel fault diagnosis approach grounded in quantum Q-learning is presented in this paper. …”
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Audio Adversarial Example Detection Using the Audio Style Transfer Learning Method by Hyun Kwon, Kangjun Lee, Junyeol Ryu, Jun Lee

“…In this paper, we propose a method for defending against audio adversarial examples that operates by applying audio style transfer learning. …”
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