A machine learning-based model for predicting survival in patients with Rectosigmoid Cancer. by Yifei Wang, Bingbing Chen, Jinhai Yu

“…After evaluating each model, the prediction model based on XGBoost was determined to be the optimal model, with AUC of 0.7856, 0.8484, and 0.796 at 1, 3, and 5 years. …”
Get full text

Monthly Water Level Prediction Based on ESMD-VMD-ESN Hybrid Model by LI Ang, ZHANG Kun, SANG Yuting, BI Wan

“…Water level sequence contain complex features of multiple frequency information.To improve the prediction accuracy of the water level sequences,a combined model was developed based on Extreme-point Symmetric Mode Decomposition (ESMD),Variational Mode Decomposition (VMD) and Echo State Network (ESN),namely ESMD-VMD-ESN.And it was applied to forecast water level of the Taipuzha station in the upper reaches of Taipu River.The predictive effect of the “first decomposition-second decomposition-prediction-reconstruction” model was explored by comparing it with a single model ESN and the combination model ESMD-ESN.The results show that ESMD-VMD-ESN has the highest accuracy,followed by ESMD-ESN,and the lowest ESN accuracy.Compared with the ESN,the Willmott's Index of Agreement (WIA) and Pearson Correlation Coefficient (PCC) of ESMD-ESN respectively increased by 51% and 11%,the Mean Absolute Error (MAE) and Root Mean Squard Error (RMSE) of ESMD-ESN respectively decreased by 14% and 45%.ESMD can effectively simplify the water level sequence and reduce the prediction error.Compared with the ESMD-ESN,the WIA and PCC of ESMD-VMD-ESN respectively increased by 5% and 10%,the MAE and RMSE of ESMD-ESN respectively decreased by 52% and 50%.VMD can further simplify the highest frequency component of ESMD and improving the model prediction accuracy.In conclusion,the combined model ESMD-VMD-ESN has well applicability and stability in the monthly water level prediction.…”
Get full text

Failure prediction of T-peel adhesive joints by different cohesive laws and modelling approaches by Alessandro Pirondi

Get full text

Navigating tenses in Bengali sentences: A stacked ensemble model for enhanced prediction by Umme Ayman, Md. Nahid Hasan, Ms. Nusrat Khan, Ms. Chayti Saha, Md. Fayejullah

Get full text

Integrated clinical and proteomic-based model for diagnostic and prognostic prediction in pRCC by Zeya Xu, Linhui Zhang, Jiacheng Lyu, Maoping Cai, Tao Ji, Lin Bai, Liqing Li, Yao Zhu, Huashan Xu, Subei Tan, Hualei Gan, Shujuan Ni, Wenhao Xu, Xi Tian, Aihetaimujiang Anwaier, Beiyan Liu, Qinqin Hou, Guohai Shi, Hailiang Zhang, Jianyuan Zhao, Dingwei Ye, Yuanyuan Qu, Chen Ding

“…In summary, this study provides a comprehensive plasma proteomic analysis and establishes diagnostic and prognostic predictive models for pRCC.…”
Get full text

Machine learning prediction model for lateral lymph node metastasis in rectal cancer by Longchun Dong, Shiyong Du, Hongjie Yang, Hongjie Yang, Hongjie Yang, Hongjie Yang, Xipeng Zhang, Xipeng Zhang, Xipeng Zhang, Xipeng Zhang, Zhichun Zhang, Zhichun Zhang, Zhichun Zhang, Zhichun Zhang, Shuan Geng, Shuan Geng, Shuan Geng, Shuan Geng, Yuanda Zhou, Yuanda Zhou, Yuanda Zhou, Yuanda Zhou, Peng Li, Peng Li, Peng Li, Peng Li, Qingsheng Zeng, Qingsheng Zeng, Qingsheng Zeng, Qingsheng Zeng, Yi Sun, Yi Sun, Yi Sun, Yi Sun, Peishi Jiang

“…The R software was used to create a logistic prediction model and a nomogram.ResultsThis study included 66 pathologically positive and 77 pathologically negative lateral lymph node cases. …”
Get full text

Reconstruction and Prediction of Regional Population Migration Neural Network Model with Age Structure by Cuiying Li, Yulin Wu, Yi Cheng, Yandong Guo, Kun Wei, Jie Zhao

“…Based on artificial neural networks, this article proposes a class of population models with age structure described by partial differential equations to predict the future trends of regional population changes. …”
Get full text

Indirect modeling of derived outcomes: Are minor prediction discrepancies a cause for concern? by John P. Prybylski

“…Because these derivations are indirectly predicted from the model, they are valuable tests for misspecification when used in visual or numeric predictive checks (V/NPCs). …”
Get full text

An efficient method for predicting the morphology of proppant packs based on a surrogate model by Tao ZHANG, Hangyu ZHOU, Yifan ZHANG, Jianchun GUO, Haoran GOU, Tang TANG

“…Through correlation analysis, the primary factors influencing these characteristic parameters were identified. Intelligent proxy models for the prediction of proppant placement patterns were established on the basis of the cascade neural network, including a time-concentration model for predicting particle volume fraction and a displacement-height model for predicting particle placement height. …”
Get full text

IVIM-DWI-based radiomic model for preoperative prediction of hepatocellular carcinoma differentiation by ZHUANG Yuxiang, LI Xiaofeng, ZHOU Daiquan

“…Among all models, the predictive performance of the radiomic model and the radiomic-clinical combined model was better than that of the clinical model. …”
Get full text

Machine learning-based e-commerce platform repurchase customer prediction model. by Cheng-Ju Liu, Tien-Shou Huang, Ping-Tsan Ho, Ping-Tsan Ho, Jui-Chan Huang, Ching-Tang Hsieh

“…In this paper, we first combine the single model, and then use the model fusion algorithm to fuse the prediction results of the single model. …”
Get full text

Adaptive machine learning framework: Predicting UHPC performance from data to modelling by Yinzhang He, Shaojie Gao, Yan Li, Yongsheng Guan, Jiupeng Zhang, Dongliang Hu

“…Ultra-High Performance Concrete (UHPC) is vital for next-generation infrastructure, necessitating complex interaction modeling beyond empirical methods. This study proposes an interpretable machine learning (ML) framework to predict the compressive strength (CS) of UHPC and analyze input variable influences. …”
Get full text

Thermal conduction behavior and prediction model of scrap tire rubber-sand mixtures by Tao Zhang, Yang Chen, Yu-Ling Yang, Cai-Jin Wang, Guo-Jun Cai

“…Several series of thermal probe tests were conducted on scrap rubber tire-sand mixtures with varied rubber contents, moisture contents, and dry densities. A predictive model was proposed by resorting to the artificial neural network technology to capture the thermal conductivity data. …”
Get full text

Evaluation of Lightning Prediction by an Electrification and Discharge Model in Long-Term Forecasting Experiments by Liangtao Xu, Shuang Chen, Wen Yao

“…The predictability of the model was enhanced with increasing thunderstorm scale. …”
Get full text

Establishment of Fracture Prediction Model of Muti-point Incremental Forming on Sheet Material by XIAO Hong-li, CAI Gai-pin, QI Bu-chun, ZHOU Xiao-lei

Subjects: Get full text

Research on Financial Stock Market Prediction Based on the Hidden Quantum Markov Model by Xingyao Song, Wenyu Chen, Junyi Lu

“…The model was used to predict 15 stock indices from the Shanghai and Shenzhen Stock Exchanges between June 2018 and June 2021. …”
Get full text

Using the LARS-WG Model to Predict the Maximum Temperature in Zakho City, Iraq by Sura Abdulsahib, Salah Zubaidi, Nadheer Ayoob

“…The predicted increase for the maximum temperature ranges between 1.4 to 2.7 ºC. …”
Get full text

Advanced air quality prediction using multimodal data and dynamic modeling techniques by Umesh Kumar Lilhore, Sarita Simaiya, Rajesh Kumar Singh, Abdullah M. Baqasah, Roobaea Alroobaea, Majed Alsafyani, Afnan Alhazmi, M. D. Monish Khan

“…The attention mechanism directs the model’s focus to the most informative features, improving predictive accuracy. …”
Get full text

Research on Deformation Prediction of Foundation Pit Based on PSO-GM-BP Model by Dongge Cui, Chuanqu Zhu, Qingfeng Li, Qiyun Huang, Qi Luo

“…The results show that both the GM (1, 1) and BP neural network models can predict accurate results. The prediction optimized by the particle swarm algorithm is more accurate and has more substantial applicability. …”
Get full text

Predicting oxytocin binding dynamics in receptor genetic variants through computational modeling by Preeti Dubey, Yingye Fang, K. Lionel Tukei, Shobhan Kuila, Xinming Liu, Annika Sahota, Antonina I. Frolova, Erin L. Reinl, Manasi Malik, Sarah K. England, Princess I. Imoukhuede

Get full text