TMS: Ensemble Deep Learning Model for Accurate Classification of Monkeypox Lesions Based on Transformer Models with SVM by Elsaid Md. Abdelrahim, Hasan Hashim, El-Sayed Atlam, Radwa Ahmed Osman, Ibrahim Gad

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A machine learning model for predicting anatomical response to Anti-VEGF therapy in diabetic macular edema by Wenrui Lu, Kunhong Xiao, Xuemei Zhang, Yuqing Wang, Wenbin Chen, Xierong Wang, Yunxi Ye, Yan Lou, Li Li

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A scoping review and modelling of predictors of an abnormal Thompson score in term neonates in low-resource settings by Khan Nushrat, Mugwagwa Edna, Cortina-Borja Mario, Catherall Ellie, Fitzgerald Felicity, Chimhuya Simbarashe, Chimhini Gwendoline, Gannon Hannah, Crehan Caroline, Mangiza Marcia, Heys Michelle

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Construction of a sleep staging prediction model for obstructive sleep apnea patients based on hypoxia parameters by YANG Mengdie，PENG Cheng，CUI Yiran，XU Shaorong，WANG Yan

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Machine learning applications in placenta accreta spectrum disorders by Mahsa Danaei, Maryam Yeganegi, Sepideh Azizi, Fatemeh Jayervand, Seyedeh Elham Shams, Mohammad Hossein Sharifi, Reza Bahrami, Ali Masoudi, Amirhossein Shahbazi, Amirmasoud Shiri, Heewa Rashnavadi, Kazem Aghili, Hossein Neamatzadeh

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Machine learning in predicting immediate and long-term outcomes of myocardial revascularization: a systematic review by B. I. Geltser, V. Yu. Rublev, M. M. Tsivanyuk, K. I. Shakhgeldyan

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Assessing the potential distribution of Myracrodruon urundeuva Allemão (Aroeira) in the Caatinga under climate change scenarios by Douglas Batista da Costa, Robson Borges de Lima, Rinaldo L. Caraciolo Ferreira, Alessandro de Paula, Cinthia Pereira de Oliveira, José A. Aleixo da Silva, Joselane P. Gomes, Mariana M. M. Santana, Ana Luisa L. Pereira

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Study on an interpretable prediction model for pile bearing capacity based on SHAP and BP neural networks by Shunbo Li, Mingwei Hai, Qi Zhang, Bin Zhou, Miao Wang, Zhuo Zhao

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A Hybrid Intelligent Model for Olympic Medal Prediction Based on Data-Intelligence Fusion by Ning Li, Junhao Li, Hejia Fang, Jian Wang, Qiao Yu, Yafei Shi

“…This study presents a hybrid intelligent model for predicting Olympic medal distribution at the 2028 Los Angeles Games, based on data-intelligence fusion (DIF). …”
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Machine-learning model for predicting left atrial thrombus in patients with paroxysmal atrial fibrillation by Wanli Xiong, Qiqi Cao, Lu Jia, Min Chen, Tao Liu, Qingyan Zhao, Yanhong Tang, Bo Yang, Li Li, Shaobo Shi, He Huang, Congxin Huang, China Atrial Fibrillation Center Project Team

“…Conclusion This simplified prediction model effectively identifies the risk of LAT in patients with paroxysmal AF, providing a valuable tool for clinical decision-making. …”
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Preliminary investigation on predicting postoperative glioma recurrences based on a multiparametric radiomics model by Fang-Xiong Fu, Fang-Xiong Fu, Guo Li, Lan Hong, Wang-Sheng Chen

“…This study aimed to evaluate the performance of a magnetic resonance imaging (MRI)-based multiparametric radiomics model for the early prediction of postoperative recurrences.MethodsThe data from 60 patients who met the inclusion criteria between 2000 and 2021 were collected in this study. …”
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A preoperative pathological staging prediction model for esophageal cancer based on CT radiomics by Haojun Li, Shuoming Liang, Mengxuan Cui, Weiqiu Jin, Xiaofeng Jiang, Simiao Lu, Jicheng Xiong, Hainan Chen, Ziwei Wang, Guotai Wang, Jiming Xu, Linfeng Li, Yao Wang, Haomiao Qing, Yongtao Han, Xuefeng Leng

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Heart Failure Prediction Based on Bootstrap Sampling and Weighted Fusion LightGBM Model by Yuanni Wang, Hong Cao

“…The purpose of this study is to establish a more suitable prediction model of heart disease. Based on LightGBM, we have deeply integrated bootstrap sampling and weighting technology. …”
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Research on the Prediction Model of Mine Subsidence Based on Object-Oriented and Probability Integration Method by Zhongyuan Gu, Yanlin Zhao, Rugao Gao, Lewen Wu

“…MATLAB2019 is used to develop the application program of the prediction model, the reliability of the prediction model is tested by engineering cases, and the main influencing factors of mining subsidence are analyzed at the same time. …”
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Application of a KAN-LSTM Fusion Model for Stress Prediction in Large-Diameter Pipelines by Zechao Li, Shiwei Qin

“…By modifying the fully connected layer of the original LSTM model, we develop a novel LSTM-KAN model and evaluate its performance through comprehensive predictive analysis. …”
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A novel deep learning model for predicting marine pollution for sustainable ocean management by Michael Onyema Edeh, Surjeet Dalal, Musaed Alhussein, Khursheed Aurangzeb, Bijeta Seth, Kuldeep Kumar

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A numerical model based on ALE formulation to predict crack propagation in sandwich structures by Marco Francesco Funari, Fabrizio Greco, Paolo Lonetti, Saverio Spadea

“…A numerical model to predict crack propagation phenomena in sandwich structures is proposed. …”
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Application of disease prediction model in chronic kidney disease complicated with contrast induced nephropathy by ZHOU Min, ZHOU Ying, XU Xiao-jin, ZHU Ying, CHEN Min, WANG Guo-yi, ZHANG Qing, ZHANG Xiao-bo

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Spectral Data-Driven Prediction of Soil Properties Using LSTM-CNN-Attention Model by Yiqiang Liu, Luming Shen, Xinghui Zhu, Yangfan Xie, Shaofang He

“…This study presents an LSTM-CNN-Attention model that integrates temporal and spatial feature extraction with attention mechanisms to improve predictive accuracy. …”
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A Prediction Method and Model Experiments on Surf-Riding and Broaching in Stern-Quartering Waves by Jilong Chu, Min Gu, Jiang Lu, Peijie Zhang

“…Accurately and efficiently predicting surf-riding and broaching remains a key problem to be solved for the direct stability assessment of surf-riding and broaching. …”
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