A Starved Lubrication Model: Applications to Evaluate Gear Mesh and Response Prediction of Material Plasticity by Zhiyong Wang, Qingbing Dong, Bo Zhao

“…This study presents a model of starved mixed Elastohydrodynamic Lubrication (EHL) in point and line contact to investigate the lubrication performance and material response. …”
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A Precise Prediction Method for Subsurface Temperatures Based on the Rock Resistivity–Temperature Coupling Model by Ri Wang, Guoshu Huang, Jian Yang, Lichao Liu, Wang Luo, Xiangyun Hu

“…Unfortunately, such approximations often introduce substantial errors, undermining the reliability and precision of the predictions. We present an advanced prediction methodology for deep temperature fields based on the rock resistivity–temperature coupling model (RRTCM). …”
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Gaussian Versus Mean-Field Models: Contradictory Predictions for the Casimir Force Under Dirichlet–Neumann Boundary Conditions by Daniel Dantchev, Vassil Vassilev, Joseph Rudnick

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Predicting Heart Rate Slow Component Dynamics: A Model Across Exercise Intensities, Age, and Sex by Massimo Teso, Alessandro L. Colosio, Maura Loi, Jan Boone, Silvia Pogliaghi

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Enhancing heart disease prediction accuracy by comparing classification models employing varied feature selection techniques by Balliu Lorena, Zanaj Blerina, Basha Gledis, Zanaj Elma, Meçe Elinda Kajo

“…It includes the analysis of different algorithms such as Decision Tree, Logistic Regression, Support Vector Machine, Random Forest and hybrid models. This results in SVM and RM performing better after applying feature selection for individual ML models. …”
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PHYSICS-DRIVEN FEATURE CREATION TO IMPROVE MACHINE LEARNING MODELS PERFORMANCE FOR OIL PRODUCTION RATE PREDICTION by Eghbal Motaei, Seyed Mehdi Tabatabai, Tarek Ganat, Ahmad Khanifar, Sulaiman Dzaiy, Timur Chis

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Prediction of the Trimer Protein Interface Residue Pair by CNN-GRU Model Based on Multi-Feature Map by Yanfen Lyu, Ting Xiong, Shuaibo Shi, Dong Wang, Xueqing Yang, Qihuan Liu, Zhengtan Li, Zhixin Li, Chunxia Wang, Ruiai Chen

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Multi-Task Trajectory Prediction Using a Vehicle-Lane Disentangled Conditional Variational Autoencoder by Haoyang Chen, Na Li, Hangguan Shan, Eryun Liu, Zhiyu Xiang

“…Trajectory prediction under multimodal information is critical for autonomous driving, necessitating the integration of dynamic vehicle states and static high-definition (HD) maps to model complex agent–scene interactions effectively. …”
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Sleep Stage Classification Through HRV, Complexity Measures, and Heart Rate Asymmetry Using Generalized Estimating Equations Models by Bartosz Biczuk, Sebastian Żurek, Szymon Jurga, Elżbieta Turska, Przemysław Guzik, Jarosław Piskorski

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Optimal Weighting Factors Design for Model Predictive Current Controller for Enhanced Dynamic Performance of PMSM Employing Deep Reinforcement Learning by Muhammad Usama, Amine Salaje, Thomas Chevet, Nicolas Langlois

“…This paper presents a novel control strategy employing a deep reinforcement learning (DRL) scheme for online selection of optimal weighting factors in cost functions of the finite control set model predictive current controller of a permanent magnet synchronous motor (PMSM). …”
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Adaptive Model Predictive Control for 4WD-4WS Mobile Robot: A Multivariate Gaussian Mixture Model-Ant Colony Optimization for Robust Trajectory Tracking and Obstacle Avoidance by Hayat Ait Dahmad, Hassan Ayad, Alfonso García Cerezo, Hajar Mousannif

“…This study uses a nonlinear model predictive controller (MPC) to ensure accurate trajectory tracking of a four-wheel drive, four-wheel steer (4WD-4WS) mobile robot. …”
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Sensitivity Analysis of Soil Hydraulic Parameters for Improved Flow Predictions in an Atlantic Forest Watershed Using the MOHID-Land Platform by Dhiego da Silva Sales, Jader Lugon Junior, David de Andrade Costa, Renata Silva Barreto Sales, Ramiro Joaquim Neves, Antonio José da Silva Neto

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Implementation of Principal Component Analysis (PCA)/Singular Value Decomposition (SVD) and Neural Networks in Constructing a Reduced-Order Model for Virtual Sensing of Mechanical... by M. A. Melgarejo, A. Pérez, D. Ruiz, A. Casas, F. González, V. González de Lena Alonso

“…The ROM is constructed through neural networks trained on Finite Element Method (FEM) outputs from multiple scenarios, resulting in a simplified yet highly accurate model that can be easily implemented digitally. The ANN model achieves a prediction error of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>MAE</mi><mi>test</mi></msub><mo>=</mo><mrow><mo>(</mo><mn>0.04</mn><mo>±</mo><mn>0.06</mn><mo>)</mo></mrow><mo> </mo><mi>MPa</mi></mrow></semantics></math></inline-formula> for the instantaneous mechanical stress predictions, evaluated over the entire range of stress values (0 to 5.32 MPa) across the component structure. …”
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Enhancing Hospitalized Patients' Palliative Care Referrals via Machine Learning-Based Predictive Modeling within Electronic Health Record Systems by Arun Ghoshal

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Analysis and Application of Critical Pressure Prediction Model for Surface Leakage of Underwater Shallow Buried Jacking-Pipe Grouting by Ziguang Zhang, Yong He, Xiaopeng Li, Xiang Li, Lin Wei, Feifei Chen

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A spatiotemporal model for urban taxi Origin–Destination prediction based on Multi-hop GCN and Hierarchical LSTM by Jiang Rong, Wangtu Xu, Yanjie Wen

“…Our model and dataset are open sourced at https://github.com/YanJieWen/OD-STGCN.…”
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PrediQt-Cx: post treatment health related quality of life prediction model for cervical cancer patients. by Satwant Kumar, Madhu Lata Rana, Khushboo Verma, Narayanjeet Singh, Anil Kumar Sharma, Arun Kumar Maria, Gobind Singh Dhaliwal, Harkiran Kaur Khaira, Sunil Saini

“…The objectives of the study were to compare the pre and the post treatment quality of life in cervical cancer patients and to develop a prediction model to provide an insight into the possibilities in the treatment modules.…”
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Prediction of Seawater Intrusion Run-Up Distance Based on <i>K</i>-Means Clustering and ANN Model by Jiatao Li, Zhenzhu Meng, Junkang Zhang, Yukai Chen, Jiewen Yao, Xinyue Li, Peng Qin, Xian Liu, Chunmei Cheng

“…The model’s performance is demonstrated through a high <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mi>R</mi><mn>2</mn></msup></semantics></math></inline-formula> value of 0.97 and low mean squared error (MSE) of 0.0092, surpassing traditional ANN models in its ability to capture complex wave dynamics.…”
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A machine learning model for predicting lymph node positivity in ovarian cancer: development, validation, and clinical application by QingYong Guo, Jinji Wang, Ru Chen, LiPing Hu, Wenqiang You

“…Tumor size ≥5 cm, histological subtype, and chemotherapy were key predictive features, with SHAP analysis identifying tumor size as the most influential factor.ConclusionWe present the first machine learning model specifically developed for predicting lymph node positivity in OC, validated across large, diverse cohorts. …”
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Development and validation of a nomogram model for predicting the occurrence of necrotizing enterocolitis in premature infants with late-onset sepsis by Min Tao, Ling Yan, Yu Lang, Leilei Shen, Sheng Chen, Na Cai

“…R software was used to establish the nomogram prediction model. Internal validation was performed by bootstrapping 1,000 resamples to assess model stability. …”
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