Rail Degradation Prediction Models for Tram System: Melbourne Case Study by Amir Falamarzi, Sara Moridpour, Majidreza Nazem, Reyhaneh Hesami

“…Two different models including a regression model and an Artificial Neural Networks (ANN) model have been applied for predicting tram track gauge deviation. …”
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Developing serum proteomics based prediction models of disease progression in ADPKD by Hande Ö. Aydogan Balaban, Sita Arjune, Franziska Grundmann, Jan-Wilm Lackmann, Thomas Rauen, Philipp Antczak, Roman-Ulrich Müller

“…A comparison to an Immunoglobulin A nephropathy cohort provides information regarding the eGFR-dependency and disease specificity of these proteins. The final outcome prediction model (adjusted R² 0.31) contains six proteins, namely Endothelial Plasminogen Activator Inhibitor (SERPINF1), Glutathione Peroxidase 3 (GPX3), Afamin (AFM), FERM Domain Containing Kindlin-3 (FERMT3), Complement Factor H Related 1 (CFHR1), and Retinoic Acid Receptor Responder 2 (RARRES2), the predictive value of which is independent from the clinical and imaging parameters currently used in clinical care. …”
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Mine pressure prediction based on empirical mode decomposition linear model by Yuwei ZHU, Pengfei WANG, Huixian WANG, Qiangqiang NIU, Liang XIN

“…To ensure the safe and efficient extraction of coal mines and reduce sudden roof accidents, this study proposes a novel multivariate long-term sequence mine pressure prediction model—the Empirical Mode Decomposition Linear Model (EMD–Mixer). …”
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Deep Learning Model for Prediction of Dementia Severity based on EEG Signals by Noor Kamal Al-Qazzaz, Sawal Hamid Bin Mohd Ali, Siti Anom Ahmad

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Short-Term Wind Speed Prediction Using EEMD-LSSVM Model by Aiqing Kang, Qingxiong Tan, Xiaohui Yuan, Xiaohui Lei, Yanbin Yuan

“…Furthermore, the scatter diagrams of predicted versus actual wind speed and histograms of prediction errors are presented to verify the superiority of the hybrid model in short-term wind speed prediction.…”
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Construction of ubiquitination-related risk model for predicting prognosis in lung adenocarcinoma by Dawei Sun, Xiaohong Duan, Ning Li, Ou Qiao, Yingjie Hou, Zihuan Ma, Siyao Liu, Yanhua Gong, Zichuan Liu

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Statistical and machine learning models for predicting university dropout and scholarship impact. by Stephan Romero, Xiyue Liao

“…First, we aim to build predictive models to learn of the significant socioeconomic and academic features associated with students' dropout risk. …”
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Innovative Study on Volatility Prediction Model for New Energy Stock Indices by Yanguo Li, Chao Long

“…To address this, this paper proposes a deep learning ensemble model based on decomposition optimization for predicting the volatility of new energy stock indices. …”
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Bayesian Model Prediction for Breast Cancer Survival: A Retrospective Analysis by Islam Bani Mohammad, Muayyad M. Ahmad

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A theoretical model for predicting the Peak Cutting Force of conical picks by Gao Kuidong, Du Changlong, Jiang Hongxiang, Liu Songyong

“…In order to predict the PCF (Peak Cutting Force) of conical pick in rock cutting process, a theoretical model is established based on elastic fracture mechanics theory. …”
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Soft Computing Models to Predict Pavement Roughness: A Comparative Study by Panos Georgiou, Christina Plati, Andreas Loizos

“…The comparative study of the developed models concludes that the performance of the ANN model is slightly better compared to the SVM in terms of prediction accuracy. …”
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Dynamic tire-pavement friction prediction with an integrated sensing-modeling approach by Baiyu Jiang, Xunjie Chen, Hao Wang, Jingang Yi

“…This study proposed an intelligent tire solution to predict tire-pavement friction from tire sensors using an integrated modeling-sensing approach. …”
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Establishment and validation of a model for predicting depression risk in stroke patients by Fangbo Lin, Meiyun Zhou

“…Calibration plots confirmed high predictive accuracy, while DCA revealed substantial clinical utility. …”
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Uncertainties in the finite-time Lyapunov exponent in an ocean ensemble prediction model by M. Matuszak, J. Röhrs, P. E. Isachsen, P. E. Isachsen, M. Idžanović

“…Generally, trajectory simulations, such as Lagrangian trajectories, inherit uncertainty from the underlying ocean model, bearing substantial uncertainties as a result of chaotic and turbulent flow fields. …”
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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

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Design and Implementation of an LSTM Model with Embeddings on MCUs for Prediction of Meteorological Variables by Jhan Piero Paulo Merma Yucra, David Juan Cerezo Quina, German Alberto Echaiz Espinoza, Manuel Alejandro Valderrama Solis, Daniel Domingo Yanyachi Aco Cardenas, Andrés Ortiz Salazar

“…The use of recurrent neural networks has proven effective in time series prediction tasks such as weather. However, their use in resource-limited systems such as MCUs presents difficulties in terms of both size and stability with longer prediction windows. …”
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Application and Comparative Study of Large Language Model in Early Prediction of Glaucoma by Xu Manyi

“…This paper aims to explore and compare the application effects of several advanced large language models in the early prediction of glaucoma. The study selected a variety of large language models, including Chat Generative Pre-trained transformer (ChatGPT), to build a glaucoma prediction model and analyze clinical data, genetic information, and lifestyle data of patients. …”
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Predicting clinical trial duration via statistical and machine learning models by Joonhyuk Cho, Qingyang Xu, Chi Heem Wong, Andrew W. Lo

“…We apply survival analysis as well as machine learning models to predict the duration of clinical trials using the largest dataset so far constructed in this domain. …”
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Construction and application of gold price prediction model based on historical data by Xing Xuexia, Yan Qingqing, Wang Yutong

“…This article delves into the methods and practices of building gold price prediction models based on historical data. Predictive models were constructed using machine learning methods such as random forests and BP neural networks by collecting and preprocessing data on gold prices and related economic indicators from September 2022 to December 2023. …”
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Development and validation of a model for predicting myopia in young children in China by Ting Hu, Rong Wu, Xi He, Zi-Yu Hua, Tian-Li Peng, Xiao-Yan Peng, Shi-Ming Li

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