Predicting depressive symptoms through social support: a machine learning approach in military populations by Kun-Huang Chen, Pao-Lung Chiu, Ming-Hsuan Chen

“…Five ML classifiers, Random Forest, Decision Tree, Support Vector Machine (SVM), AdaBoost, and k-Nearest Neighbors, were applied to predict depressive symptoms, with model performance evaluated across full and subgroup samples.Results: The Random Forest model achieved the highest area under the precision-recall curve (AUPRC) at 96.3% and consistently outperformed other classifiers across a range of evaluation metrics. …”
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Classification of Toraja Wood Carving Motif Images Using Convolutional Neural Network (CNN) by Nurilmiyanti Wardhani, Billy Eden William Asrul, Antonius Riman Tampang, Sitti Zuhriyah, Abdul Latief Arda

“…The methodology in this study involves adjusting the batch size during the model training phase and applying weak-to-strong pixel transformation during the double threshold hysteresis phase in the Canny Feature Extraction process on the edges of Toraja carving images, resulting in ResNet50 architecture accurately recognizing the patterns of Toraja wood carvings. …”
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Coral reef detection using ICESat-2 and machine learning by Gabrielle A. Trudeau, Kim Lowell, Jennifer A. Dijkstra

“…Future work should refine algorithms and incorporate additional environmental variables to improve model performance across various reef types.…”
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AI-driven multi-agent reinforcement learning framework for real-time monitoring of physiological signals in stress and depression contexts by Thanveer Shaik, Xiaohui Tao, Lin Li, Haoran Xie, Hong-Ning Dai, Feng Zhao, Jianming Yong

“…The study evaluates the proposed system using two real-world datasets-PPG-DaLiA and WESAD-designed to capture physiological and stress-related data. The performance is compared with baseline models, including Q-Learning, PPO, Actor-Critic, Double DQN, and DDPG, as well as existing monitoring frameworks like WISEML and CA-MAQL. …”
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Analysis of imaging signatures in 18F-DOPA PET of glioblastoma treated with dose-escalated radiotherapy by Jing Qian, Deanna H. Pafundi, William G. Breen, Paul D. Brown, Christopher H. Hunt, Mark S. Jacobson, Derek R. Johnson, Timothy J. Kaufmann, Bradley J. Kemp, Sani H. Kizilbash, Val J. Lowe, Michael W. Ruff, Jann N. Sarkaria, Joon H. Uhm, Joon H. Uhm, Mark J. Zakhary, Maasa H. Seaberg, Hok Seum Wan Chan Tseung, Elizabeth S. Yan, Yan Zhang, Nadia N. Laack, Debra H. Brinkmann

“…Multivariates cox analysis was performed to assess the prognostic value of delta features in survival analysis.ResultsThe pre-irradiation features demonstrated predictive capability in distinguishing survival groups, yielding an accuracy of 0.78 on the reserved test dataset. …”
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Prediction of prognosis of immune checkpoint inhibitors combined with anti-angiogenic agents for unresectable hepatocellular carcinoma by machine learning-based radiomics by Xuni Xu, Xue Jiang, Haoran Jiang, Xiaoye Yuan, Mengjing Zhao, Yuqi Wang, Gang Chen, Gang Li, Yuxia Duan

“…Methods 111 patients with uHCC were enrolled in this study. After performing univariate cox regression and the least absolute shrinkage and selection operator (LASSO) algorithms to extract radiological features, the Rad-score was calculated through a Cox proportional hazards regression model and a random survival forest (RSF) model. …”
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A Stacking Ensemble Framework Leveraging Synthetic Data for Accurate and Stable Crop Yield Forecasting by Muhammad Waqar, Yong-Woon Kim, Yung-Cheol Byun

“…OSEM incorporates hyperparameter tuning and dimensionality reduction using Singular Value Decomposition to enhance predictive performance and reduce feature noise. Extensive experiments on globally distributed and region-specific crop datasets demonstrate that OSEM consistently outperforms both SEM and state-of-the-art baselines, achieving <inline-formula> <tex-math notation="LaTeX">$R^{2} = 0.996$ </tex-math></inline-formula> and MAE = 0.185 t/ha. …”
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ESMII-Net: An edge-synergy and multidimensional information interaction network for remote sensing change detection by Yixin Chen, Xiaogang Ning, Ruiqian Zhang, Hanchao Zhang, Xiao Huang, You He

“…To overcome these challenges, we introduce the Edge-Synergy and Multidimensional Information Interaction Network (ESMII-Net) specifically designed for remote sensing change detection. We achieve feature enhancement through the Multidimensional Information Interaction Fusion Module (MIIFM) and, by integrating the edge aware decoder and the Edge-Synergy Module (ESM), guide the model to acquire effective edge information, thereby improving change detection performance. …”
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PSYCHOLOGICAL AND PEDAGOGICAL BASES OF FORMATION OF THE FUTURE SPECIALISTS’ INDIVIDUAL STYLE OF PROFESSIONAL ACTIVITIES by Lavrentieva Olena, Krupskyi Oleksandr

“…A complex of research methods has been used, namely: content analysis, generalization and specification in the provisions of the theory of activity and professional pedagogy regarding the essence of the individual style of activity, modelling of the structure of the individual style of professional activity, substantiating the pedagogical terms of its formation in future specialists during their professional preparation process. …”
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2bRAD-M reveals circulating microbiome in chronic antibody-mediated rejection (CAMR) and IgA nephropathy (IgAN) after kidney transplantation by Yan-Xin Tao, Er-Di Zhang, Jia-Xi Yue, Zheng-Li Wan, Ji-Wen Fan, Yi Li, Yu Fan, Lin Yan

“…The alpha diversity of CAMR and IgAN was all higher than STABLE, there are also differences in beta diversity. LEfSe was performed to identify different abundance taxa, 21 discriminative features between CAMR and STABLE, 39 discriminative features between IgAN and STABLE. …”
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Sentiment Analysis of X Application Users on Bitcoin Using the Naïve Bayes Method Optimized with Particle Swarm Optimization (PSO) by Raja Allifin Muhammad, Elin Haerani, Fitri Wulandari, Lola Oktavia

“…Model performance was evaluated using accuracy, precision, recall, and F1-score metrics. …”
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Attention-GANs: An Advanced GNSS Data Augmentation Method for Improved NLOS/LOS Classification by S. Nie, H. Yang

“…This imbalance reduces model generalization, leading to biased predictions. …”
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Real-Time Implementation of a Microcontroller-Based Coupled-Tank Water Level Control System with Feedback Linearization and Fuzzy Logic Controller Algorithms by Bahadir Yesil, Savas Sahin

“…The CTS model is developed using physical parameters obtained from a real experimental setup. …”
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Comparative Analysis of a Quantum SVM With an Optimized Kernel Versus Classical SVMs by Matheus Cammarosano Hidalgo

“…Experiments varied the number of variables from two to seven to evaluate their impact on model performance and kernel behavior. The experiments were conducted on quantum simulators, which faced scalability challenges addressed using reduced datasets. …”
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Intrusion Detection-Data Security Protection Scheme Based on Particle Swarm-BP Network Algorithm in Cloud Computing Environment by Zhun Wang, Xue Chen

“…Then, by introducing the decision tree algorithm, the overfitting is reduced and the data processing speed of the model is improved, and on this basis, the feature selection is carried out through the “gain rate” optimization method, which reduces the redundant information of the feature vector. …”
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Multi-Step Dynamic Ensemble Selection to Estimate Software Effort by Akshay Jadhav, Shishir Kumar Shandilya, Ivan Izonin, Roman Muzyka

“…The paper utilized four software effort datasets discretized into labeled effort ranges. The performance of the proposed model is evaluated based on the K nearest neighbor oracle (KNORA) canonical approach to DES and in order to reduce the complexity, filter feature selection techniques are applied to extract the relevant feature set. …”
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A Multi-Branch Convolution and Dynamic Weighting Method for Bearing Fault Diagnosis Based on Acoustic–Vibration Information Fusion by Xianming Sun, Yuhang Yang, Changzheng Chen, Miao Tian, Shengnan Du, Zhengqi Wang

“…This model aims to enhance feature fusion, dynamically adapt to signal characteristics, optimize feature selection, and reduce computational complexity. …”
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Unified interest point detection and description for perspective and Fisheye images by Jian Xu, DeWei Han, Kang Li, JunJie Li, ZhaoYuan Ma

“…We propose a method for generating fisheye data, and inspired by SuperPoint, we modify the network architecture for feature extraction and descriptor generation. By employing nearest neighbor (NN) matching, our proposed dataset generation method improves the performance of the original SuperPoint network, while the network architecture introduced in this paper further improves overall performance.…”
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A New Quantum Circuits of Quantum Convolutional Neural Network for X-Ray Images Classification by Mohammed Yousif, Belal Al-Khateeb, Begonya Garcia-Zapirain

“…A MNIST and covidx-cxr3 datasets was used to train quantum-CNN models, and the results of these comparisons were made with traditional CNN performance. …”
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DEMNet: A Small Object Detection Method for Tea Leaf Blight in Slightly Blurry UAV Remote Sensing Images by Yating Gu, Yuxin Jing, Hao-Dong Li, Juntao Shi, Haifeng Lin

“…In response to this problem, this paper proposes DEMNet, a model based on the YOLOv8n architecture. The goal is to enhance small, blurry object detection performance in UAV-based scenarios. …”
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