Evaluating ensemble models for fair and interpretable prediction in higher education using multimodal data by Felipe Emiliano Arévalo-Cordovilla, Marta Peña

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A mathematical model for predicting the spatiotemporal response of breast cancer cells treated with doxorubicin by Hugo J. M. Miniere, Ernesto A. B. F. Lima, Guillermo Lorenzo, David A. Hormuth II, Sophia Ty, Amy Brock, Thomas E. Yankeelov

“…We present a data assimilation-prediction pipeline with a two-phenotype model that includes a spatiotemporal component to characterize and predict the evolution of in-vitro breast cancer cells and their heterogeneous response to chemotherapy. …”
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AMFGNN: an adaptive multi-view fusion graph neural network model for drug prediction by Fang He, Fang He, Fang He, Fang He, Lian Duan, Lian Duan, Lian Duan, Lian Duan, Guodong Xing, Guodong Xing, Guodong Xing, Guodong Xing, Xiaojing Chang, Xiaojing Chang, Xiaojing Chang, Xiaojing Chang, Huixia Zhou, Huixia Zhou, Huixia Zhou, Huixia Zhou, Mengnan Yu, Mengnan Yu, Mengnan Yu, Mengnan Yu

“…However, existing methods for drug-disease association prediction still face limitations in feature representation, feature integration, and generalization capabilities.MethodsTo address these challenges, we propose a novel model named AMFGNN (Adaptive Multi-View Fusion Graph Neural Network). …”
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A web-based surveillance model of eosinophilic meningitis: future prediction and distribution patterns by Noppadol Aekphachaisawat, Kittisak Sawanyawisuth, Chalongchai Phitsanuwong, Sittichai Khamsai, Paiboon Chattakul, Verajit Chomtmongkol, Somsak Tiamkao, Panita Limpawattana, Vichai Senthong, Jarin Chindaprasirt, Chetta Ngamjarus

“…Results: we developed autoregressive integrated moving average (ARIMA) models and seasonal ARIMA (SARIMA) models. The best model was used for predicting numbers of future cases. …”
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Development of an early mortality risk prediction model for pediatric patients with secondary hemophagocytic lymphohistiocytosis by Nandu Luo, Guangli Yang, Pingping Zhang, Baoli Li, Yan Chen, Zuochen Du, Pei Huang

“…Abstract Background To establish a visual prediction model for the risk of early mortality in pediatric patients with secondary hemophagocytic lymphohistiocytosis (sHLH). …”
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Prediction of polar motion and UT1-UTC based on the hybrid EEMD_LSTM model by Chenxiang Wang, Pengfei Zhang, Wenbin Shen, Jiayao Wang

“…Therefore, the ERPs prediction with high accuracy is very significant. Conventional approaches to predicting ERPs are mainly based on the linear models. …”
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CNN–Patch–Transformer-Based Temperature Prediction Model for Battery Energy Storage Systems by Yafei Li, Kejun Qian, Qiuying Shen, Qianli Ma, Xiaoliang Wang, Zelin Wang

“…Experiments conducted on two real-world residential BESS datasets demonstrate that the proposed model achieved superior prediction accuracy compared to models such as Informer and iTransformer across temperature prediction tasks with various horizon lengths. …”
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Comparative Analysis of Machine Learning Models for Predicting Contaminant Concentration Distributions in Hospital Wards by Chonggang Zhou, Yunfei Ding

“…Four common machine learning models—multiple linear regression (MLR), support vector regression (SVR), backpropagation (BP) neural network, and convolutional neural network (CNN)—were employed to predict the distribution of contaminants within the wards. …”
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Model error propagation in a compatible tree volume, biomass, and carbon prediction system by James A. Westfall, Philip J. Radtke, David M. Walker, John W. Coulston

“…As these attributes are typically predicted from statistical models, frameworks that provide compatible relationships among these attributes are usually preferred over approaches that provide independent predictions. …”
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An interpretable coupled model (SWAT-STFT) for multispatial-multistep evapotranspiration prediction in the river basin by Zhonghui Guo, Chang Feng, Liu Yang, Qing Liu

“…This integration of physics-based and data-driven modeling not only provides valuable insights into watershed ET modeling prediction and mechanistic understanding but also underscores the broader potential for application across global watersheds and related disciplines.…”
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Forecasting Civil Aviation Incident Rate in China Using a Combined Prediction Model by Yixiang Sun, Nana Geng

“…Then, it used the smallest sum of squared errors as the principle to use a combined prediction model based on the IOWA operator. It can be seen from the experimental results that the prediction accuracy of the combined model is better than single models. …”
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Prediction model for psychological disorders in ankylosing spondylitis patients based on multi-label classification by Kun Yang, Yifan Gong, Xiaohan Xu, Tiantian Sun, Xinning Qu, Xiaxiu He, Hongxiao Liu

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ARIMA-Kriging and GWO-BiLSTM Multi-Model Coupling in Greenhouse Temperature Prediction by Wei Zhou, Shuo Liu, Junxian Guo, Na Liu, Zhenglin Li, Chang Xie

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Climate change projections and hydrological modelling to predict the streamflow in Berach-Banas catchment, Rajasthan by Kuldeep Pareta, Yogita Dashora

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Magnetic Resonance-Guided Cancer Therapy Radiomics and Machine Learning Models for Response Prediction by Jesutofunmi Ayo Fajemisin, Glebys Gonzalez, Stephen A. Rosenberg, Ghanim Ullah, Gage Redler, Kujtim Latifi, Eduardo G. Moros, Issam El Naqa

“…Various feature selection techniques and machine models interrogate the relevant radiomics features for predicting cancer treatment outcomes. …”
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A Bayesian Prediction Spatial Model for Confirmed Dengue Cases in the State of Chiapas, Mexico by Manuel Solís-Navarro, Cruz Vargas-De-León, María Gúzman-Martínez, Josselin Corzo-Gómez

“…Therefore, this study aimed to develop and validate a simple Bayesian prediction spatial model for the state of Chiapas, Mexico. …”
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Numerical Prediction of Solid Particle Erosion in Jet Pumps Based on a Calibrated Model by Xuanchen Wan, Mengxue Dong, Maosen Xu, Chuanhao Fan, Jiegang Mou, Shuai Han

“…The CFD-DEM method was used to simulate the solid–liquid two-phase flow in the jet pump, comparing six erosion models for predicting erosion rates. The Grey Wolf Optimization algorithm was applied to calibrate model coefficients. …”
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Model prediction of inactivation of Aeromonas salmonicida grown on poultry in situ by intense pulsed light by Jingwen Wang, Zhenzhen Ning, Yifan Chen, Xinglian Xu, Huhu Wang

“…And further a secondary model between the scale factor b and the treatment voltage in Weibull model was established using linear equations, which determined that the secondary model could accurately predict the inactivation of A. salmonicida. …”
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A methodological systematic review of validation and performance of sepsis real-time prediction models by Zichen Wang, Wen Wang, Che Sun, Jili Li, Shuangyi Xie, Jiayue Xu, Kang Zou, Yinghui Jin, Siyu Yan, Xuelian Liao, Yan Kang, Craig M. Coopersmith, Xin Sun

“…Abstract Sepsis real-time prediction models (SRPMs) provide timely alerts and may improve patient outcomes but face limited clinical adoption due to inconsistent validation methods and potential biases. …”
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MACHINE LEARNING MODELS FOR PERFORMANCE PREDICTION OF YOUNG PLAYERS IN FOOTBALL ACADEMIES – A REVIEW by Armand Florin Bertea, Cezar Honceriu

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