Prediction of recurrence after surgery for pituitary adenoma using machine learning- based models: systematic review and meta-analysis by Ibrahim Mohammadzadeh, Bardia Hajikarimloo, Behnaz Niroomand, Nasira Faizi, Pooya Eini, Mohammad Amin Habibi, Alireza Mohseni, Mohammadmahdi Sabahi, Abdulrahman Albakr, Michael Karsy, Hamid Borghei-Razavi

“…Abstract Background Predicting pituitary adenoma (PA) recurrence after surgical resection is critical for guiding clinical decision-making, and machine learning (ML) based models show great promise in improving the accuracy of these predictions. …”
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Machine Learning Model Based on Prognostic Nutritional Index for Predicting Long‐Term Outcomes in Patients With HCC Undergoing Ablation by Nan Zhang, Ke Lin, Bin Qiao, Liwei Yan, Dongdong Jin, Daopeng Yang, Yue Yang, Xiaohua Xie, Xiaoyan Xie, Bowen Zhuang

“…ABSTRACT Aims To develop multiple machine learning (ML) models based on the prognostic nutritional index (PNI) and determine the optimal model for predicting long‐term survival outcomes in hepatocellular carcinoma (HCC) patients after local ablation. …”
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Inflow Prediction for Agricultural Reservoirs Using Disaster Prevention Measurement Data: A Comparison of TANK Model and Machine Learning by Bong-Kuk Lee, Joonyoung Choi, Kyoung Jae Lim, Jeongho Han

“…The results of this study demonstrate the potential of machine learning techniques for inflow prediction in agricultural reservoirs and suggest the need for further research on model improvement using various algorithms and input variables.…”
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Soft Computing Techniques to Model the Compressive Strength in Geo-Polymer Concrete: Approaches Based on an Adaptive Neuro-Fuzzy Inference System by Zhiguo Chang, Xuyang Shi, Kaidan Zheng, Yijun Lu, Yunhui Deng, Jiandong Huang

“…Additionally, the model’s performance was compared with the existing literature, showing significant improvements in predictive accuracy and robustness. …”
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Sensitive Multispectral Variable Screening Method and Yield Prediction Models for Sugarcane Based on Gray Relational Analysis and Correlation Analysis by Shimin Zhang, Huojuan Qin, Xiuhua Li, Muqing Zhang, Wei Yao, Xuegang Lyu, Hongtao Jiang

“…Subsequently, three supervised learning algorithms—Gradient Boosting Decision Tree (GBDT), Random Forest (RF), and Support Vector Machine (SVM)—were employed to develop both single-stage and multi-stage yield prediction models. …”
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Route Generation and Built Environment Behavioral Mechanisms of Generation Z Tourists: A Case Study of Macau by Ying Zhao, Pohsun Wang, Yafeng Lai

“…Building on this behavioral mechanism, an interest-based Ant Colony Optimization (ACO) algorithm is implemented by incorporating point-of-interest (POI) preferences and distance matrices to improve personalized route generation. …”
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Multistation Wind Speed Forecasting Based on Dynamic Spatiotemporal Graph Convolutional Networks by Jianhong Gan, Runqing Kang, Xun Deng, Chentao Mao, Zhibin Li, Peiyang Wei, Chunjiang Wu, Tongli He

“…Finally, the particle swarm optimization algorithm is used for hyperparameter optimization to improve the prediction accuracy. …”
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Transmission Line Anomaly Detection and Real-Time Monitoring System Combining Edge Computing and EfficientDet by Menghao Lin, Yang Ding, Tianle Wang, Yang Liu, Zewei Li

“…In the target recognition part, an improved EfficientDet algorithm is adopted as the main body, and the aspect ratio of anchor boxes in the algorithm is optimized using K-means clustering algorithm. …”
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Force-Driven Model for Automated Clear Aligner Staging Design Based on Stepwise Tooth Displacement and Rotation in 3D Space by Sensen Yang, Yumin Cheng

“…This innovative method substantially improved design efficiency and accuracy, ultimately elevating the efficacy of clear aligner therapy, although further biomechanical analyses and experimental validations are needed to refine the model parameters.…”
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The Design, Creation, Implementation, and Study of a New Dataset Suitable for Non-Intrusive Load Monitoring by Carlos Rodriguez-Navarro, Francisco Portillo, Francisco G. Montoya, Alfredo Alcayde

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Enhancing phase change thermal energy storage material properties prediction with digital technologies by Minghao Yu, Jing Liu, Cheng Chen, Mingyue Li

“…To address these limitations, the integration of digital technologies, such as computational modeling and machine learning (ML), has become increasingly important.MethodsThis paper proposes a hybrid multiscale modeling framework that integrates molecular dynamics (MD) simulations, finite element methods (FEM) from continuum mechanics, and supervised ML algorithms—including deep neural networks and gradient boosting regressors—to enable accurate and efficient prediction of material properties across scales. …”
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CHPOA-DBN Transformer Fault Diagnosis Method Considering Sample Within-Class Imbalance by Shuang WANG, Qian LUO, Bo TANG, Lan JIANG, Jin LI

“…Then, the Tent chaotic map embedded chaotic hybrid pelican optimization algorithm (CHPOA) is developed to optimize the number of hidden layer nodes and reverse fine-tuning learning rate of DBN, and the CHPOA-DBN transformer fault diagnosis model is constructed. …”
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Advanced intrusion detection technique (AIDT) for secure communication among devices in internet of medical things (IoMT) by M. Ramya, Pradeep Sudhakaran, Yuvaraj Sivagnanam, C. Santhana Krishnan

“…By employing the integrated patient sensing and network traffic datasets, our research achieves a superior accuracy rate of 96.4% in network intrusion detection compared to the competing algorithms. Furthermore, we incorporated a comprehensive analysis of the implementation of different classification algorithms in IoMT network intrusion detection, further supporting the claim that the proposed framework performs marginally better than alternative models.…”
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Adaptive dynamic programming-based multi-fault tolerant control of reconfigurable manipulator with input constraint by Zhenguo Zhang, Tianhao Ma, Yadan Zhao, Shuai Yu, Fan Zhou

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Anti-disturbance predictive control for path tracking of unmanned agricultural vehicles based on safety distance by HUANG Zhenzhen, SUN Jinlin, DING Shihong

“…Building on this, the cost function is integrated with lateral offset and heading offset information, combined with the obstacle avoidance penalty function, and an anti-disturbance model predictive control scheme is constructed by solving the nonlinear constrained optimization problem online. …”
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Anti-disturbance predictive control for path tracking of unmanned agricultural vehicles based on safety distance by HUANG Zhenzhen, SUN Jinlin, DING Shihong

“…Building on this, the cost function is integrated with lateral offset and heading offset information, combined with the obstacle avoidance penalty function, and an anti-disturbance model predictive control scheme is constructed by solving the nonlinear constrained optimization problem online. …”
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Research on the Stability of Express Delivery Supply Chain Based on Risk Propagation Model ------ Case Studies of SF Express and JD Logistics by Fan Yunhui

“…Based on the research results, optimization strategies such as dynamic path optimization algorithms and blockchain-based information isolation mechanisms are proposed, providing theoretical tools and practical references for risk prevention and control in the express delivery industry.…”
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DDoSNet: Detection and prediction of DDoS attacks from realistic multidimensional dataset in IoT network environment by Goda Srinivasa Rao, P. Santosh Kumar Patra, V.A. Narayana, Avala Raji Reddy, G.N.V. Vibhav Reddy, D. Eshwar

“…Following this, feature selection uses the African Buffalo Optimization with Decision Tree (ABO-DT) method. This nature-inspired metaheuristic algorithm imitates the behaviour of African buffalos to determine which traits are the most important. …”
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Adaptive drive-based integration technique for predicting rheological and mechanical properties of fresh gangue backfill slurry by Chaowei Dong, Jianfei Xu, Nan Zhou, Jixiong Zhang, Hao Yan, Zejun Li, Yuzhe Zhang

“…Analysis demonstrates that the particle swarm optimal (PSO) algorithm based on adaptive adjustment strategy can effectively optimize the hyperparameters of support vector regression (SVR), and the MC-PSO-SVR model exhibits better predictive capability (R2> 0.88) and lower error coefficients (MAE, RSE, and RMSE values approaching 0) and narrower widths of 95 % confidence intervals for yield stress, plastic viscosity, fluidity, and UCS. …”
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Adaptive average arterial pressure control by multi-agent on-policy reinforcement learning by Xiaofeng Hong, Walid Ayadi, Khalid A. Alattas, Ardashir Mohammadzadeh, Mohamad Salimi, Chunwei Zhang

“…Abstract The current research introduces a model-free ultra-local model (MFULM) controller that utilizes the multi-agent on-policy reinforcement learning (MAOPRL) technique for remotely regulating blood pressure through precise drug dosing in a closed-loop system. …”
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