Stroke Dataset Modeling: Comparative Study of Machine Learning Classification Methods by Kalina Kitova, Ivan Ivanov, Vincent Hooper

“…Their Random Forest (RF) classifier, combined with Feature Importance (FI) selection, achieved an accuracy of 97.17%, illustrating the positive impact of RF and relevant feature selection on model performance. …”
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Machine Learning Models for Predicting Thermal Properties of Radiative Cooling Aerogels by Chengce Yuan, Yimin Shi, Zhichen Ba, Daxin Liang, Jing Wang, Xiaorui Liu, Yabei Xu, Junreng Liu, Hongbo Xu

“…This study presents a machine-learning-based model for predicting the performance of radiative cooling aerogels (RCAs). …”
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GNSS Precipitable Water Vapor Prediction for Hong Kong Based on ICEEMDAN-SE-LSTM-ARIMA Hybrid Model by Jie Zhao, Xu Lin, Zhengdao Yuan, Nage Du, Xiaolong Cai, Cong Yang, Jun Zhao, Yashi Xu, Lunwei Zhao

“…Finally, the prediction results of the three components are linearly combined to obtain the final prediction value. To validate the model performance, experiments were conducted using measured GNSS-PWV data from several stations in Hong Kong. …”
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Presenting a prediction model for HELLP syndrome through data mining by Boshra Farajollahi, Mohammadjavad Sayadi, Mostafa Langarizadeh, Ladan Ajori

“…Then, patient records were gathered, and in the third stage, the dataset was preprocessed and prepared for modeling. Finally, ML models were implemented, and their evaluation metrics were compared. …”
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Generalized domain prompt learning for accessible scientific vision-language models by Qinglong Cao, Yuntian Chen, Lu Lu, Hao Sun, Zhengzhong Zeng, Xiaokang Yang, Dongxiao Zhang

“…By leveraging small-scale domain-specific foundation models and minimal prompt samples, the framework enriches the language component with domain-specific knowledge through quaternion networks, revealing cross-modal relationships between specialized vision features and natural vision-based contextual embeddings. …”
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Gearbox Fault Diagnosis Based on the LMD Cloud Model and PSO-KELM by Zhao Xiaohui, Tan Qi, Hu Sheng, Yang Wenbin, Huan Kaixuan, Zhang Zhijie

“…To address this problem, a gearbox fault diagnosis method based on local mean decomposition (LMD) cloud model feature extraction combined with particle swarm optimization (PSO) kernel extreme learning machine (KELM) is proposed. …”
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Hyperspectral Estimation of Tea Leaf Chlorophyll Content Based on Stacking Models by Jinfeng Guo, Dong Cui, Jinxing Guo, Umut Hasan, Fengqi Lv, Zixing Li

“…In this study, derivative transformations were first applied to preprocess the tea hyperspectral data, followed by the use of the Stable Competitive Adaptive Reweighted Sampling (SCARS) algorithm for feature variable selection. Finally, multiple individual machine learning models and stacking models were constructed to estimate tea LCC based on hyperspectral data, with a particular emphasis on analyzing how the selection of base models and meta-models affects the predictive performance of the stacking models. …”
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Water quality anomaly detection research based on GRU-PINN model by Zhao Xinyu

“…Feature selection is then performed based on feature importance ranking and mutual information analysis. …”
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Development of an upper limb muscle strength rehabilitation assessment system using particle swarm optimisation by Chuangan Zhou, Siqi Wang, Meiyi Wu, Wei Lai, Junyu Yao, Xingyue Gou, Hui Ye, Jun Yi, Dong Cao

“…Model performance was evaluated using R-squared (R2), Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Mean Bias Error (MBE).ResultsThe system successfully collected electromyographic and kinematic data. …”
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Local Differential Privacy Graph Data Modeling Method for Link Prediction by HANQilong, WUXiaoming

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Deep Neural Network-Based Detection of Modulated Jamming in Free-Space Optical Systems: Theory and Performance Under Atmospheric Fading by Manav R. Bhatnagar

“…Results show that the proposed model approaches the theoretical limit at moderate dimensions, low noise, and high jammer power, while generalization performance is constrained at large dimensions by data sparsity and architectural capacity. …”
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MODELING OF THREE-PHASE THREE LEG TRANSFORMER DEVICES FOR ENGINEERING CALCULATIONS OF ASYMMETRICAL MODES FOR DIFFERENT SCHEMES OF WINDING CONNECTIONS by Bosneaga V.A, Suslov V.M.

“…The model is proposed for the calculation and research of steady state asymmetric modes and transients in three-phase three legs transformer devices with arbitrary diagram of windings connection, taking into account the electromagnetic coupling of the windings, located on different legs. …”
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Exploring UAV Networking From the Terrain Information Completeness Perspective: A Tutorial by Zhengying Lou, Ruibo Wang, Baha Eddine Youcef Belmekki, Mustafa A. Kishk, Mohamed-Slim Alouini

“…When terrain information is incomplete, and only terrain-related feature parameters are available, we discuss how existing models map terrain features to blockage probabilities. …”
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Development and validation of interpretable machine learning models for postoperative pneumonia prediction by Bingbing Xiang, Yiran Liu, Shulan Jiao, Wensheng Zhang, Shun Wang, Mingliang Yi

“…We successfully established nine machine learning models for predicting postoperative pneumonia in surgical patients, with the general linear model demonstrating the best overall performance. …”
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An Ensemble Model for Predicting Cardiovascular Disease utilizing Nature Inspired Optimization by Annwesha Banerjee Majumder, Somsubhra Gupta, Sourav Majumder, Dharmpal Singh

“…The application of the BAT method in this particular model has yielded a notable improvement in performance, resulting in an accuracy rate of 84.94%. …”
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Gaussian-binary restricted Boltzmann machines for modeling natural image statistics. by Jan Melchior, Nan Wang, Laurenz Wiskott

“…We present a theoretical analysis of Gaussian-binary restricted Boltzmann machines (GRBMs) from the perspective of density models. The key aspect of this analysis is to show that GRBMs can be formulated as a constrained mixture of Gaussians, which gives a much better insight into the model's capabilities and limitations. …”
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Construction of VAE-GRU-XGBoost intrusion detection model for network security. by Yu Chen, Xiaohong Zheng, Nan Wang

“…When the sample sizes were 10000 and 40000, the shortest time and longest feature extraction time of the model were 0.030s and 0.112s, respectively. …”
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A Robust Stacking-Based Ensemble Model for Predicting Cardiovascular Diseases by Hayat Bihri, Lalla Amina Charaf, Salma Azzouzi, My El Hassan Charaf

“…Results: Experimental results indicate that the MLP-based stacking model achieves superior performance, with an accuracy of 97.06%, outperforming existing approaches reported in the literature. …”
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Adaptive neuro-fuzzy inference systems for improved mastitis classification and diagnosis by Javad Shirani Shamsabadi, Saeid Ansari Mahyari, Mostafa Ghaderi-Zefrehei

“…Two feature reduction techniques were used to reduce data dimensions and improve model performance: Pearson correlation and principal component analysis. …”
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Model-based Bayesian Fusion-Net for infrared and visible image fusion by Wang Li, Kuang Yafang, Cai Ziyi, Chu Ning, Mohammad-Djafari Ali

“…By formulating image fusion as an inverse problem within a hierarchical Bayesian framework, our method leverages physical priors and data-driven techniques to enhance model interpretability and transferability. Compared to traditional and deep learning-based fusion methods, the proposed Bayesian Model-based Fusion-Net achieves promising performance with significantly reduced computational complexity (0.07G FLOPs). …”
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