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Construction of an oligometastatic prediction model for nasopharyngeal carcinoma patients based on pathomics features and dynamic multi-swarm particle swarm optimization support ve...
Published 2025-06-01“…ObjectiveThis study aimed to develop a risk prediction model for post-treatment oligometastasis in nasopharyngeal carcinoma (NPC) by integrating pathomics features and an improved Support vector machine (SVM) algorithm, offering precise early decision support.MethodsThis study retrospectively included 462 NPC patients, without or with oligometastasis defined by ESTRO/EORTC criteria. …”
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Optimizing concrete strength: How nanomaterials and AI redefine mix design
Published 2025-07-01“…XGB was identified as the most effective ML algorithm for predicting compressive strength among others in this study (R2=0.974). …”
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Conveyor X-Ray Tomosynthesis Imaging With Optimized Structured Sequential Illumination
Published 2020-01-01Get full text
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Technique on Vehicle Damage Assessment After Collisions Using Optical Radar Technology and Iterative Closest Point Algorithm
Published 2024-01-01“…We apply the Iterative Closest Point (ICP) algorithm and Singular Value Decomposition (SVD) methods, along with a proposed deep learning neural network optimization model, to perform point cloud alignment between the pre-collision and post-collision vehicle models. …”
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Study on Optimal Decision of Unit Commitment with Flexible Reserve Participation in Power Grid
Published 2023-06-01Get full text
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Determination of Optimal Parameters of the Ground Filling During the Laying of Power Cable Lines
Published 2025-04-01“…The model that has been developed takes into account the influence of both normal and post-emergency operation modes. …”
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Research on Stability Optimization for Automatic Train Operation of Heavy-haul Trains of Baoshen Railway
Published 2024-04-01“…This paper presents an optimization control algorithm based on a dynamic evaluation model of train states, tailored to the specific conditions and operational requirements of the Shenmu-Shuozhou Railway. …”
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Integrating vision transformer-based deep learning model with kernel extreme learning machine for non-invasive diagnosis of neonatal jaundice using biomedical images
Published 2025-07-01“…Finally, the enhanced coati optimization algorithm (ECOA) method is implemented for the hyperparameter tuning of the KELM method, which results in a higher classification process. …”
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Sustainable supply chain: An optimization and resource efficiency in additive manufacturing for automotive spare part
Published 2025-06-01“…Leveraging genetic algorithm techniques for optimization and reinforced by rigorous numerical analysis, its efficacy and validity are robustly demonstrated.…”
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Underwater Acoustic Signal Prediction Based on MVMD and Optimized Kernel Extreme Learning Machine
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A Comparative Analysis of Hyper-Parameter Optimization Methods for Predicting Heart Failure Outcomes
Published 2025-03-01“…The XGBoost models exhibited moderate improvement (+0.01683) post-validation. …”
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RE-YOLOv5: Enhancing Occluded Road Object Detection via Visual Receptive Field Improvements
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Deep learning algorithm on H&E whole slide images to characterize TP53 alterations frequency and spatial distribution in breast cancer
Published 2024-12-01“…Traditional ancillary methods like immunohistochemistry (IHC) to assess TP53 functionality face pre- and post-analytical challenges. This proof-of-concept study employed a deep learning (DL) algorithm to predict TP53 mutational status from H&E-stained whole slide images (WSIs) of BC tissue. …”
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Comparative Study on Hyperparameter Tuning for Predicting Concrete Compressive Strength
Published 2025-06-01“…This study assesses the impact of hyperparameter optimization algorithms on the performance of machine learning-based concrete compressive strength prediction models. …”
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Optimized actuator design for flapping-wing robots: A multi-objective approach to mimic natural flapping dynamics
Published 2025-04-01“…The optimization utilized the NSGA-II algorithm. Additionally, a virtual prototype with rigid-flexible coupling was created for simulation assessments pre- and post-optimization. …”
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