Machine learning and SHAP value interpretation for predicting comorbidity of cardiovascular disease and cancer with dietary antioxidants by Xiangjun Qi, Shujing Wang, Caishan Fang, Jie Jia, Lizhu Lin, Tianhui Yuan

“…Objective: To develop and validate a machine learning model incorporating dietary antioxidants to predict cardiovascular disease (CVD)-cancer comorbidity and to elucidate the role of antioxidants in disease prediction. Methods: Data were sourced from the National Health and Nutrition Examination Survey. …”
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The Assessment of Participatory Scenario Planning in Future-Study of the Environment in District 1, Tehran City by Aiub Maroofi, Jila Sajadi, Mohammadtaghi Razavian

“…The data analysis of the questionnaire shows that the significance level for the three indicators of citizenship awareness, environmental behavior and citizenship accountability among the two research groups is less than 0.05, which indicates that the participants in the compilation environmental scenarios are environmentally friendly and require themselves to do the routines in accordance with the protection and promotion of the environment of their habitat. …”
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The Characteristic of Measles Epidemic Process in Kyrgyz Republic by M. S. Niiazalieva, O. V. Tsvirkun, V. S. Toygombaeva, I. Sh. Aldjambaeva, G. S. Ishenapysova, R. A. Frolov, G. S. Dadanova

“…Descriptive statistics – mean and standard error of the mean (data are presented as M ± m) for quantitative variables, for qualitative variables – determination of proportion.Results and Discussions. …”
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Wind Power Forecasting Based on Multi-Graph Neural Networks Considering External Disturbances by Xiaoyin Xu, Zhumei Luo, Menglong Feng

“…A key methodological contribution is our signal decomposition strategy during the prediction phase, where an EIF is eliminated from historical data to better learn fundamental patterns, and then a predicted EIF is reintroduced for the target period, significantly reducing error propagation. …”
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Biomass distribution law of winter wheat in mining-affected area based on UAV remote sensing by Jing WANG, Wenbing GUO, Zhichao CHEN, Erhu BAI

“…Biomass inversion models were constructed using decision tree regression (DTR), random forest regression (RFR), and support vector regression (SVR) based on field-synchronous biomass data. The best model was selected based on the coefficient of determination (R2) and root mean square error (RMSE). …”
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Research on Shale Oil Well Productivity Prediction Model Based on CNN-BiGRU Algorithm by Yuan Pan, Xuewei Liu, Fuchun Tian, Liyong Yang, Xiaoting Gou, Yunpeng Jia, Quan Wang, Yingxi Zhang

“…Hyperparameter optimization via grid searching yielded optimal configurations, while field applications demonstrated operational feasibility. Comparative analysis revealed a mean relative error (MRE) of 16.11% between predicted and observed production values, substantiating the model’s predictive competence. …”
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Parents' Attitudes Toward COVID-19 Vaccination for School Children in Jordan by Ahlam Abo Zaid, Mohammad Mahmoud Suliman, Mohammed ALBashtawy, Wafa' Ta’an, Mean Aljezawi, Asem Abdalrahim, Abdullah Alkhawaldeh

“…Statistical Package for the Social Sciences (SPSS) version 17 facilitated data analysis, incorporating descriptive and inferential statistics at a significance level of 0.05, with a 5% margin of error. …”
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Evaluating the total laboratory testing process and performance via quality indicators in clinical chemistry and hematology laboratories at Pawi General Hospital, Benishangul Gumz,... by Nigatu Tarekegn, Aklilu Getachew Mamo, Kedir Abdella Abdulsemed, Seid Abrar Abdlshikure, Zeleke Mekonnen

“…Chi-square analysis revealed a statistically significant difference in the frequency of errors across the three phases (χ2 = 4986, p < 0.0001). …”
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Estimating Heart Rate from Inertial Sensors Embedded in Smart Eyewear: A Validation Study by Sarah Solbiati, Federica Mozzini, Jean Sahler, Paul Gil, Bruno Amir, Niccolò Antonello, Diana Trojaniello, Enrico Gianluca Caiani

“…SmartEW showed high agreement with ECG, especially with QI threshold equal to 70, as a trade-off between accuracy, low error, and acceptable data coverage (80%). Correlation for QI ≥ 70 was high across all the experimental phases (r² up to 0.96), and the accuracy within ±5 bpm reached 95%. …”
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Levenberg-Marquardt recurrent neural network for heat transfer in ternary hybrid nanofluid flow with nonlinear heat source-sink by Ibrahim Mahariq, Kashif Ullah, Mehreen Fiza, Aasim Ullah Jan, Hakeem Ullah, Saeed Islam, Seham M. Al-Mekhlafi

“…A numerical stochastic approach is applied to evaluate training (TR), mean square errors (MSE), performance (PF), and data fitting (FT). …”
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Multi-scale machine learning model predicts muscle and functional disease progression by Silvia S. Blemker, Lara Riem, Olivia DuCharme, Megan Pinette, Kathryn Eve Costanzo, Emma Weatherley, Jeff Statland, Stephen J. Tapscott, Leo H. Wang, Dennis W. W. Shaw, Xing Song, Doris Leung, Seth D. Friedman

“…Feature analysis revealed that metrics of fat heterogeneity within muscle predicts muscle-level progression. …”
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A Hybrid Strategy-Improved SSA-CNN-LSTM Model for Metro Passenger Flow Forecasting by Jing Liu, Qingling He, Zhikun Yue, Yulong Pei

“…To address the issues of slow convergence and large errors in existing metaheuristic algorithms when optimizing neural network-based subway passenger flow prediction, we propose the following improvements. …”
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A machine-learning-based approach for active monitoring of blade pitch misalignment in wind turbines by S. Milani, J. Leoni, S. Cacciola, A. Croce, M. Tanelli

“…Additionally, regression analysis proves the capability of the framework to detect misalignments as low as 0.1° with a root mean square error of 5.48 %. …”
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Population Pharmacokinetic Modeling of the Oral Calcitonin Gene‐Related Peptide Receptor Antagonist Rimegepant in Adults by Craig M. Comisar, Jim H. Hughes, Jose Francis, Yorinao Chinda, Yamato Sano, Chieko Muto, Christine Neumar, Rajinder Bhardwaj, Richard Bertz, Jing Liu

“…Plasma concentration‐time data were analyzed using nonlinear mixed effects modeling. …”
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Towards MR-Only Radiotherapy in Head and Neck: Generation of Synthetic CT from Zero-TE MRI Using Deep Learning by Souha Aouadi, Mojtaba Barzegar, Alla Al-Sabahi, Tarraf Torfeh, Satheesh Paloor, Mohamed Riyas, Palmira Caparrotti, Rabih Hammoud, Noora Al-Hammadi

“…This study investigates the generation of synthetic CT (sCT) images from zero echo time (ZTE) MRI to support MR-only radiotherapy, which can reduce image registration errors and lower treatment planning costs. Since MRI lacks the electron density data required for accurate dose calculations, generating reliable sCTs is essential. …”
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Adaptation of the process‐based CSM‐CROPGRO model to simulate the growth and development of industrial hemp for seed and fiber production by Alwin Hopf, Kenneth J. Boote, Yogendra Upadhyaya, Hardeep Singh, Michael J. Mulvaney, Navdeep Kaur, Lakesh K. Sharma, Zachary Brym, Jonathan A. Watson, Gerrit Hoogenboom

“…Future work should include a more detailed observation and mechanistic simulation of self‐thinning and evaluation with data representing different production environments and cultivars. …”
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Strategies for Soil Salinity Mapping Using Remote Sensing and Machine Learning in the Yellow River Delta by Junyong Zhang, Xianghe Ge, Xuehui Hou, Lijing Han, Zhuoran Zhang, Wenjie Feng, Zihan Zhou, Xiubin Luo

“…Notably, under Strategy IX, the SVR model achieved the best predictive performance, with a coefficient of determination (R²) of 0.62 and a root mean square error (RMSE) of 0.38 g/kg. Analysis based on SHapley Additive exPlanations (SHAP) values and feature importance indicated that Vegetation Type Factors contributed significantly and consistently to the model’s performance, maintaining higher importance than traditional salinity indices and playing a dominant role. …”
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RivAIr: A custom-designed UAV-based sensor for real-time water area segmentation and surface velocity estimation by Marco La Salandra, Rosa Colacicco, Simone Panza, Giovanni Fumai, Pierfrancesco Dellino, Domenico Capolongo

“…However, high computational demands and limited high-resolution river cross-section data make real-time river monitoring impractical, particularly for large or ungauged rivers during emergencies, impeding rapid analysis and decision-making. …”
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Prevalence and associated factors of myopia among school children in Bahir Dar city, Northwest Ethiopia, 2019. by Abel Sinshaw Assem, Mebratu Mulusew Tegegne, Sofonias Addis Fekadu

“…Myopia was defined as spherical equivalent refractive error of ≥ 0.5 diopter in either eye. Data were entered into Epi Info version 7 and exported to Statistical Package for Social Sciences version 23 for analysis. …”
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Investigating Two-dimensional Horizontal Mesh Grid Effects on the Eulerian Atmospheric Transport Model Using Artificial Neural Network by Amine Ajdour, Brahim Ydir, Houria Bouzghiba, Ishaq Dimeji Sulaymon, Anas Adnane, Dris Ben Hmamou, Kenza Khomsi, Jamal Chaoufi, Gábor Géczi, Radouane Leghrib

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