An interpretable electrocardiogram-based model for predicting arrhythmia and ischemia in cardiovascular disease by Tanjila Alam Sathi, Rafsan Jany, Razia Zaman Ela, AKM Azad, Salem Ali Alyami, Md Azam Hossain, Iqram Hussain

“…We designed a predictive framework utilizing boosting ML algorithms, enhanced by explainable artificial intelligence (XAI) techniques, to ensure high predictive performance in model interpretation. …”
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Modeling sediment transport on the storage capacity and life prediction of Sadpara dam by Munawwar Ali Abbas, Ahmad Cho, Muhammad Abid, Hafiz Abdul Wajid, Mukhtar Ahmed

“…The volume of water released from the Deosai River, bed slop, and the manning coefficient are concluded the contributing factors for transported sediment deposition in the reservoir. The model presented is recommended beneficial for the prediction of potential changes in the river bathymetry till 2060.…”
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Modeling and Prediction of Mixed Errors in Feed Systems Based on Digital Twins by HUANG Hua, MEI Le, ZHI Xiaobo, ZHANG Huiwang

“…These omissions lead to discrepancies between the mechanism model ’ s predictions and actual performance, ultimately affecting prediction accuracy. …”
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Topological modeling and QSPR based prediction of physicochemical properties of bioactive polyphenols by Abdul Hakeem, Asad Ullah, Shahid Zaman, Emad E. Mahmoud, Hijaz Ahmad, Parvez Ali, Melaku Berhe Belay

“…Our QSPR analysis demonstrates strong predictive correlations, highlighting the potential of graph-theoretical descriptors in rational drug design and bioactivity prediction. …”
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Predicting flavonoid physicochemical properties using topological indices and regression modeling by Huili Li, Shamaila Yousaf, Komal Shahzadi, Sobhy M. M. Ibrahim, Adnan Aslam, Guoping Zhang, Keneni Abera Tola

“…This study leverages degree-based topological indices (TIs) to predict six physicochemical properties of sixty flavonoids using linear, quadratic, and logarithmic regression models. …”
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‌Rockburst intensity grading prediction based on the LOF-ENN-KNN model‌ by Haoran Ge, Jiyong Zhang, Congbo Ma, Kai Hui, Yicong Li, Ziniu Wu

“…Aiming at the key problems in rockburst prediction, such as insufficient analysis of nonlinear correlation characteristics, significant discreteness of small sample data and limited generalization ability of traditional models, this study innovatively constructs a LOF-ENN-KNN coupling prediction model. …”
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A Robust Stacking-Based Ensemble Model for Predicting Cardiovascular Diseases by Hayat Bihri, Lalla Amina Charaf, Salma Azzouzi, My El Hassan Charaf

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Prediction Model for Brain Metastasis in Patients With Metastatic Germ‐Cell Tumors by Tareq Salous, Ryan Ashkar, Sandra K. Althouse, Clint Cary, Timothy Masterson, Nasser H. Hanna, Jennifer King, Lawrence H. Einhorn, Nabil Adra

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Prediction model for rutting of asphalt concrete pavement considering temperature influence by Wang Chuhong, Wang Zhichao

“…This study, based on Perzyna's visco-plastic theory, proposes a new elastic-viscoplastic constitutive model. This model accurately predicts the rutting deformation of asphalt concrete pavement under various temperatures and traffic load conditions through the time-temperature superposition principle. …”
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RGX Ensemble Model for Advanced Prediction of Mortality Outcomes in Stroke Patients by Jing Fang, Baoying Song, Lingli Li, Linfeng Tong, Miaowen Jiang, Jianzhuo Yan

“…Objective: This paper aims to address the clinical challenge of predicting the outcomes of stroke patients and proposes a comprehensive model called RGX to help clinicians adopt more personalized treatment plans. …”
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Career path prediction using XGBoost Model and students’ academic results by Hong Quan Nguyen, Duc Dang Khoi Nguyen, Tan Duy Le, An Mai, Kha Tu Huynh

“…After that, the algorithm uses the training subset to build the classification model. Finally, the testing subset is loaded into the model to predict each student’s career path based on the respective inputs and hyper-parameters tuning is employed to boost the model’s accuracy. …”
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Development and validation of a machine learning model for prediction of cephalic dystocia by Yumei Huang, Xuerong Ran, Xueyan Wang, Defang Wu, Zheng Yao, Jinguo Zhai

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Drought prediction based on an improved VMD-OS-QR-ELM model. by Yang Liu, Li Hu Wang, Li Bo Yang, Xue Mei Liu

“…To overcome the low accuracy, poor reliability, and delay in the current drought prediction models, we propose a new extreme learning machine (ELM) based on an improved variational mode decomposition (VMD). …”
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Design and development of an efficient RLNet prediction model for deepfake video detection by Varad Bhandarkawthekar, T. M. Navamani, Rishabh Sharma, K. Shyamala

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The Comparison of Grey System and the Verhulst Model for Rainfall and Water in Dam Prediction by Chalermchai Puripat, Sukuman Sarikavanij

“…A time series of data of rainfall in Thailand between the years 2005 and 2015 was employed to predict possible future rainfall based on Julong Deng’s grey systems theory and the grey Verhulst model to see which model can predict more accurately with uncertain and limited data. …”
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State of Charge Prediction for Electric Vehicles Based on Integrated Model Architecture by Min Wei, Yuhang Liu, Haojie Wang, Siquan Yuan, Jie Hu

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A model of group mobility management based on user behavior prediction by Xiaoyong LIN, Yang YU, Zhengkun MI

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Data-driven intelligent productivity prediction model for horizontal fracture stimulation by Qian Li, Yiyong Sui, Mengying Luo, Bin Guan, Lu Liu, Yuan Zhao

“…Finally, during fracturing design, the optimal productivity prediction model was matched to each interval based on its characteristics to predict post-fracturing productivity. …”
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A Deep Learning Model for Stroke Patients’ Motor Function Prediction by Abeer Abdulaziz AlArfaj, Hanan A. Hosni Mahmoud, Alaaeldin M. Hafez

“…The experiments depict that the best performance is attained with the incorporation of the proposed EEG-DenseNet and the transfer model. The prediction accuracy of the model reached 96.5% with reduced time computational cost. …”
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Colorectal cancer risk prediction using a simple multivariable model. by Gillian S Dite, Chi Kuen Wong, Aviv Gafni, Erika Spaeth

“…For women and men separately, we developed (i) a multivariable risk prediction model using family history, a polygenic risk score (PRS) and clinical risk factors, and (ii) a simple model comprising family history and a PRS. …”
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