Potential cerebrospinal fluid metabolomic biomarkers and early prediction model for Parkinson’s disease by Yifan Zhang, Yifan Zhang, Yuexin Yan, Xiangxu Kong, Haijun Zhang, Shengyuan Su

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Machine learning prediction of ammonia nitrogen adsorption on biochar with model evaluation and optimization by Chong Liu, Paramasivan Balasubramanian, Jingxian An, Fayong Li

“…Twelve ML models, including tree-based ensembles, kernel-based methods, and deep learning, were evaluated using Bayesian optimization and cross-validation. …”
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Application and optimization of BP prediction model driven by internet of things in tourism education by Qi Lv

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Development and validation of a nomogram model to predict the risk of strangulated intestinal obstruction by Yanjing Zhu, Qiangqiang Wang, Lvhao Cao, Tongyuan Zhang, Jiawei Chang, Xingyu Wang

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Prediction model for spontaneous combustion temperature of coal based on PSO-XGBoost algorithm by Hui Zhuo, Tongren Li, Wei Lu, Qingsong Zhang, Lingyun Ji, Jinliang Li

“…Abstract The construction of a predictive model that accurately reflects the spontaneous combustion temperature of coal in goaf is fundamental to monitoring and early warning systems for thermodynamic disasters, including coal spontaneous combustion and gas explosions. …”
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Predictive survival modelings for HIV-related cryptococcosis: comparing machine learning approaches by Xuemin Fu, Luling Wu, Luling Wu, Jingna Xun, Benno Pütz, Zhihang Zheng, Yanpeng Li, Yanpeng Li, Yinzhong Shen, Hongzhou Lu, Jun Chen, Bertram Müller-Myhsok

“…To further support clinical decision-making, we developed an elastic net regularized Cox regression model, achieving superior predictive accuracy with a mean C-index of 0.78 for 36-month outcomes and a mean Brier score of 0.13, outperforming both random survival forest and traditional Cox models. …”
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An Analytical Prediction Model of Time Diversity Performance for Earth-Space Fade Mitigation by Pantelis-Daniel M. Arapoglou, Athanasios D. Panagopoulos, Panayotis G. Cottis

“…The present work proposes a general prediction model for the application of TD by approximating the time dynamics of rain attenuation through the use of the joint lognormal distribution. …”
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Computationally efficient data‐driven model predictive control for modular multilevel converters by Muneeb Masood Raja, Haoran Wang, Muhammad Haseeb Arshad, Gregory J. Kish, Qing Zhao

“…Abstract The application of model predictive control (MPC) for the control of modular multilevel converters (MMCs) is widely explored because it offers flexibility in integrating multiobjective control and delivers superior dynamic response. …”
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Development and validation of a clinical prediction model for Clostridioides difficile associated diarrhea by Ruiying Zheng, Hewei Luan, Jun Zhou, Zhixin Shi, Xin Hong, Lei Huang, Genyan Liu

“… Introduction: The aim of this study was to develop and validate a clinical prediction model for Clostridioides difficile associated diarrhea (CDAD) based on routine laboratory tests. …”
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Spectral Energy Density in an Axisymmetric Galaxy as Predicted by an Analytical Model for the Maxwell Field by Mayeul Arminjon

“…Finally, the first predictions of the model for the spatial variation of the SED in the Galaxy are compared with those of a radiation transfer model. …”
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Vision-language model for report generation and outcome prediction in CT pulmonary angiogram by Zhusi Zhong, Yuli Wang, Jing Wu, Wen-Chi Hsu, Vin Somasundaram, Lulu Bi, Shreyas Kulkarni, Zhuoqi Ma, Scott Collins, Grayson Baird, Sun Ho Ahn, Xue Feng, Ihab Kamel, Cheng Ting Lin, Colin Greineder, Michael Atalay, Zhicheng Jiao, Harrison Bai

“…The abnormality-guided reporting strategy consistently outperformed the organ-based and holistic captioning baselines. For survival prediction, a multimodal fusion model that incorporates imaging, clinical variables, diagnostic outputs, and generated reports achieved concordance indices of 0.863 (BUH) and 0.731 (JHU), outperforming traditional PESI scores. …”
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A Forest Fire Prediction Model Based on Cellular Automata and Machine Learning by Xuan Sun, Ning Li, Duoqi Chen, Guang Chen, Changjun Sun, Mulin Shi, Xuehong Gao, Kuo Wang, Ibrahim M. Hezam

Subjects: “…Forest fire prediction…”
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Prediction and decision-making based on nonlinear risks model in stomach cancer treatment by O. V. Krasko, M. Yu. Reutovich, A. V. Ivanov

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An Improved Model Predictive Voltage Control for PMSM Drives without Motor Parameters by Xiaoguang Zhang, Ruifang Chen

Subjects: “…motor parameter-independent (mpi) prediction model…”
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Development and Validation of Prediction Model for Exhaust Emissions During Tractor Plow Tillage by Ryu-Gap Lim, Tae-Bum Kim, Wan-Soo Kim, Seung-Yun Baek, Hyeon-Ho Jeon, Jee-Young Ham, Chul Yoo, Yong-Joo Kim

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Predictive Ability of an Objective and Time-Saving Blastocyst Scoring Model on Live Birth by Bing-Xin Ma, Feng Zhou, Guang-Nian Zhao, Lei Jin, Bo Huang

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Multi-target property prediction and optimization using latent spaces of generative model by Anirudh Jain, Markus Heinonen, Heikki Käsnänen, Julius Sipilä, Samuel Kaski

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AGCN-T: A Traffic Flow Prediction Model for Spatial-Temporal Network Dynamics by Jian Feng, Lang Yu, Rui Ma

“…Aiming at the lack of the ability to model complex and dynamic spatial-temporal dependencies in current research, this paper proposes a traffic flow prediction model Attention based Graph Convolution Network (GCN) and Transformer (AGCN-T) to model spatial-temporal network dynamics of traffic flow, which can extract dynamic spatial dependence and long-distance temporal dependence to improve the accuracy of multistep traffic prediction. …”
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Research on the Large Deformation Prediction Model and Supporting Measures of Soft Rock Tunnel by Junying Rao, Yonghu Tao, Peng Xiong, Chongxin Nie, Hao Peng, Yanghao Xue, Zuowei Xi

“…Results show that the gray model has high prediction accuracy, the best prediction time is one week, and the maximum error is only 2.99%; with the decrease in d, resin bolt support has a significant supporting effect compared with mortar bolt support, with Smax.M and σmax·M reduced by 64.38% and 10.35%, respectively; as the L of bolt increases, compared with the mortar bolt support, the resin bolt support has a more obvious restraining effect on the surrounding rock deformation, and Smax·M and σmax·M are reduced by 28.20% and 10.00%, respectively; when 4.5 m < L < 6.0 m and 0.6 m < d < 0.7 m, resin bolt support should be adopted; in other ranges, mortar bolt support or resin bolt support has a less significant difference in controlling surrounding rock deformation.…”
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Predictive Model of Cesarean Hysterectomy Accompanying Cesarean Section in Patients with Placenta Previa by Myeong Gyun Choi, Jong Woon Kim, Yoon Ha Kim

“…Background: The purpose of this study was to develop a model to predict cesarean hysterectomy accompanying cesarean section in patients with placenta previa. …”
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