Comparative Analysis of Neural Network Models for Predicting Battery Pack Safety in Frontal Collisions by Jun Wang, Ouyang Chen, Zhenfei Zhan, Zhiwei Zhao, Huanhuan Bao

“…Finally, the prediction accuracy of the models was compared based on error functions. …”
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Comprehensive interaction modeling with machine learning improves prediction of disease risk in the UK Biobank by Heli Julkunen, Juho Rousu

“…In a clinical cardiovascular risk prediction scenario using the established QRISK3 model, the method adds predictive value by identifying interactions beyond the age interaction effects currently included. …”
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Reducing Judicial Inconsistency through AI: A Review of Legal Judgement Prediction Models by Wu Yifan

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Prediction Model of 30-Days Postoperative Pneumonia in Elderly Patient Undergoing Abdominal Surgery by Noto Dwimartutie, Harini Oktadiana, Gurmeet Singh, Wifanto Saditya Jeo, Kuntjoro Harimurti

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Simulate Congestion Prediction in a Wireless Network Using the LSTM Deep Learning Model by Nada Badr Jarah

“…A wireless connection was made using the Android system, and congestion was predicted based on the analysis of wireless communication packages around the access point using the LSTM deep learning model. …”
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Machine learning-based prediction of diabetic peripheral neuropathy: model development and clinical validation by Meng Sun, Xingling Sun, Fei Wang, Li Liu

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Renewable Generation (Wind/Solar) and Load Modeling through Modified Fuzzy Prediction Interval by Syed Furqan Rafique, Zhang Jianhua, Rizwan Rafique, Jing Guo, Irfan Jamil

“…In order to check the efficiency of the proposed method, a comparison is carried out with the existing models. The fuzzy interval-based model for the microgrid test bed will help to formulate the energy management problem with more accuracy and robustness.…”
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Polygenic risk scores in cardiovascular risk prediction: A cohort study and modelling analyses. by Luanluan Sun, Lisa Pennells, Stephen Kaptoge, Christopher P Nelson, Scott C Ritchie, Gad Abraham, Matthew Arnold, Steven Bell, Thomas Bolton, Stephen Burgess, Frank Dudbridge, Qi Guo, Eleni Sofianopoulou, David Stevens, John R Thompson, Adam S Butterworth, Angela Wood, John Danesh, Nilesh J Samani, Michael Inouye, Emanuele Di Angelantonio

“…The C-index, a measure of risk discrimination, was 0.710 (95% CI 0.703-0.717) for a CVD prediction model containing conventional risk predictors alone. …”
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Mathematical Model to Estimate and Predict the COVID-19 Infections in Morocco: Optimal Control Strategy by Omar Zakary, Sara Bidah, Mostafa Rachik, Hanane Ferjouchia

“…In this paper, we aim to estimate and predict the situation of the new coronavirus pandemic (COVID-19) in countries under quarantine measures. …”
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Neutrosophic Statistical Regression Models for Predicting the Incidence of Nosocomial Infections in Post-Trauma Patients by Nairovys Gómez Martinez, Gerardo Ramos Serpa, Riber Fabian Donoso Noroña, Gloria Rebeca Medina Naranjo

Subjects: “…regression models…”
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Research on a Grey Prediction Model of Population Growth Based on a Logistic Approach by Mingyu Tong, Zou Yan, Liu Chao

“…To address the disadvantages of the two models, this paper establishes a grey logistic population growth prediction model, based on the modeling mechanism of the grey prediction model and the characteristics of the logistic model, which uses the least-squares method to estimate the maximum population capacity. …”
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Using computational modeling and four-dimensional computed tomography to predict type II endoleaks by Leah M. Gober, MD, Alan Dardik, MD PhD

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Modeling the prediction of spontaneous rupture and bleeding in hepatocellular carcinoma via machine learning algorithms by Juchao Chen, Zicheng Lei, Zongcai Duan, Zhili Wen

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Deep Learning Python-Based Time-Series Model for Oil Palm Yield Prediction by Yuhao Ang, Helmi Zulhaidi Mohd Shafri, Yang Ping Lee, Shahrul Azman Bakar, Haryati Abidin, Mohd Umar Ubaydah Mohd Junaidi, Hwee San Lim, Rosni Abdullah, Yusri Yusup, Syahidah Akmal Muhammad, Teh Sin Yin

“…The application of time-series analysis in agricultural yield forecasting has gained much attention in recent years with the use of machine learning models. However, the utilization of Python-based time-series models for predicting oil palm yield remains limited. …”
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Extended sample size calculations for evaluation of prediction models using a threshold for classification by Rebecca Whittle, Joie Ensor, Lucinda Archer, Gary S. Collins, Paula Dhiman, Alastair Denniston, Joseph Alderman, Amardeep Legha, Maarten van Smeden, Karel G. Moons, Jean-Baptiste Cazier, Richard D. Riley, Kym I. E Snell

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Fault Prediction Of Pharmaceutical Air Compressor Using The Intelligent Model Based On The Bayesian Network by Mohamed AMRANI, Djamel BENAZZOUZ

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Prediction of cardiovascular disease based on multiple feature selection and improved PSO-XGBoost model by Kerang Cao, Chang Liu, Siqi Yang, Yuxin Zhang, Lili Li, Hoekyung Jung, Shuo Zhang

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WEST L-mode record long pulses guided by predictions using Integrated Modeling by T. Fonghetti, P. Manas, R. Dumont, J.-F. Artaud, C. Bourdelle, F.J. Casson, N. Cummings, L.F. Delgado-Aparicio, P. Maget, J. Morales, Y. Savoye-Peysson, M. Schneider, the WEST team

“…In particular, a reduced model for Lower-Hybrid heating and Current-Drive (LHCD) and the quasi-linear turbulent transport model TGLF are crucial for long pulses predictions up to the Last Closed Flux Surface (LCFS). …”
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Prediction Models with Multiple Linear Regression for Improving Acoustic Performance of Textile Industry Plants by Muammer YAMAN, Cüneyt KURTAY, Gülsu ULUKAVAK HARPUTLUGIL

“…The acoustic analyses of the scenario plants were performed in the ODEON Auditorium, and A-weighted sound pressure level (LA), noise reduction (NR), and reverberation time (RT) were determined. From the data, prediction equations were created with a multiple linear regression (MLR) model. …”
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Shale Gas Transition in China: Evidence Based on System Dynamics Model for Production Prediction by Yingchao Chen, Yang Zhang

“…This study employs a system dynamics model to forecast future production trends in shale gas in China, analyze its implications for the natural gas supply–demand structure, and explore pathways for sustainable development. …”
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