Interactive online learning method for students based on artificial intelligence by Cizhang Li, Wenfen Yin

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A Model Based on Neural Network to Predict Surface Settlement During Subway Station Construction: A Case Study of the Dongba-Zhongjie Station in Beijing, China by Jiaqi Zhang, Hua Jiang, Jinsen Wang, Jili Feng

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A Novel Approach for Evaluating Web Page Performance Based on Machine Learning Algorithms and Optimization Algorithms by Mohammad Ghattas, Antonio M. Mora, Suhail Odeh

“…This study introduces a novel evaluation framework for predicting web page performance, utilizing state-of-the-art machine learning algorithms to enhance the accuracy and efficiency of web quality assessment. …”
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Machine learning with the body roundness index and associated indicators: a new approach to predicting metabolic syndrome by Yaxuan He, Zekai Chen, Zhaohui Tang, Yuexiang Qin, Fang Wang

“…Conclusions The combination of BRI and machine learning provides a non-invasive and effective method for predicting MetS and offers a promising strategy for its early prevention. …”
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A Review Of Road‒Related Soil Erosion: An Assessment Of Causes, Evaluation Techniques And Available Control Measures by Khoboso Elizabeth Seutloali, Heinrich Reinhard Beckedahl

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Hybrid modeling approaches for predicting COVID-19 mortality: A comparative study across USA, France, and India by B. Uppalaiah, D. Mallikarjuna Reddy, K. Rajalakshmi, P. Vignesh, V. Govindan, Siriluk Donganont

“…The models combine the adaptability of Gaussian Processes with the deep learning functionalities of RBM, LSTM, and CNN to improve prediction precision and uncertainty assessment. We utilize various evaluation metrics to determine the optimal hybrid model: Symmetric Mean Absolute Percentage Error (sMAPE) for accuracy, Continuous Ranked Probability Score (CRPS) for probabilistic forecasts, and Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) for model selection. …”
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A multi-index evaluation system for tuff-asphalt mixtures exposed to long-term water damage based on the fractional grey prediction model. by Yanxia Cai, Jiaming Zhao, Chenchen Li, Jiachen Shi, Baoxin Zhang

“…A fractional grey prediction model (FGM) was employed to predict long-term behavior, while a comprehensive evaluation framework was developed using weighted averaging and relative scoring methods. …”
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INFLUENCE OF SIZE EFFECT ON EVALUATION OF TENSILE PROPERTIES USING SMALL PUNCH TEST (MT) by WANG WuLin, XU Tong, ZHONG JiRu, GUAN KaiShu, LIU Gang

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A Comparative Analysis of Student Performance Prediction: Evaluating Optimized Deep Learning Ensembles Against Semi-Supervised Feature Selection-Based Models by Jose Antonio Lagares Rodríguez, Norberto Díaz-Díaz, Carlos David Barranco González

“…Educational Data Mining offers analytical methods to support the prediction of student outcomes, development of intelligent tutoring systems, and curriculum optimization. …”
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Simple Clinical Prediction Rules for Identifying Significant Liver Fibrosis: Evaluation of Established Scores and Development of the Aspartate Aminotransferase-Thrombocytopenia-Alb... by Puwitch Charoenchue, Jiraporn Khorana, Apichat Tantraworasin, Suwalee Pojchamarnwiputh, Wittanee Na Chiangmai, Amonlaya Amantakul, Taned Chitapanarux, Nakarin Inmutto

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Multinational association for supportive care in cancer (MASCC) versus clinical index of stable febrile neutropenia (CISNE): evaluation of predictive performance and clinical utili... by Süleyman Alpar, Sarper Yılmaz

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Predicting implantation by using dual AI system incorporating three‐dimensional blastocyst image and conventional embryo evaluation parameters—A pilot study by Yasunari Miyagi, Toshihiro Habara, Rei Hirata, Nobuyoshi Hayashi

“…Conclusions The usefulness of the dual AI system in predicting implantation of blastocyst in handling 3D data with conventional embryo evaluation information was demonstrated. …”
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Construction and Evaluation of a Risk Prediction Model for Stress Urinary Incontinence in Late Pregnancy Based on Clinical Factors and Pelvic Floor Ultrasound Parameters by Shunlan Liu, Aizhi Huang, Yubing Huang, Linlin Hu, Lihong Cai, Shaozheng He, Guorong Lyu, Xihua Lian

“…This study aimed to evaluate the predictive value of clinical and pelvic floor ultrasound parameters for SUI and construct a validated risk model. …”
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Machine and deep learning models for predicting high pressure density of heterocyclic thiophenic compounds based on critical properties by Amir Hossein Sheikhshoaei, Ali Khoshsima

“…The leverage method showed that 99.10 percent of the data was valid. …”
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Evaluation of the impact of COVID-19 pandemic on hospital admission related to common infections: Risk prediction models to tackle antimicrobial resistance in primary care. by Ali Fahmi, Victoria Palin, Xiaomin Zhong, Ya-Ting Yang, Simon Watts, Darren M Ashcroft, Ben Goldacre, Brian MacKenna, Louis Fisher, Jon Massey, Amir Mehrkar, Seb Bacon, OpenSAFELY Collaborative, Kieran Hand, Tjeerd Pieter van Staa

“…The objectives of this study were to evaluate the impact of the COVID-19 pandemic on treatment of common infections, develop risk prediction models and examine the effects of antibiotics on infection-related hospital admissions.…”
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PTX3/NF-κB/TLR4 Pathway Evaluation in the Follicular Fluid to Successfully Predict Blastocyst Implantation: A Pilot Study by Alessio Ardizzone, Carmelo Liuzzo, Arianna Ferro, Marco Galletta, Emanuela Esposito, Anna Paola Capra

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Cross-institutional evaluation of deep learning and radiomics models in predicting microvascular invasion in hepatocellular carcinoma: validity, robustness, and ultrasound modality... by Weibin Zhang, Qihui Guo, Yuli Zhu, Meng Wang, Tong Zhang, Guangwen Cheng, Qi Zhang, Hong Ding

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Classifying the Information Needs of Survivors of Domestic Violence in Online Health Communities Using Large Language Models: Prediction Model Development and Evaluation Study by Shaowei Guan, Vivian Hui, Gregor Stiglic, Rose Eva Constantino, Young Ji Lee, Arkers Kwan Ching Wong

“…Model performance was evaluated using accuracy, recall, precision, and F1-score, along with CIs for each metric. …”
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Longitudinal Model Shifts of Machine Learning–Based Clinical Risk Prediction Models: Evaluation Study of Multiple Use Cases Across Different Hospitals by Patricia Cabanillas Silva, Hong Sun, Mohamed Rezk, Diana M Roccaro-Waldmeyer, Janis Fliegenschmidt, Nikolai Hulde, Vera von Dossow, Laurent Meesseman, Kristof Depraetere, Joerg Stieg, Ralph Szymanowsky, Fried-Michael Dahlweid

“…Thus, monitoring model shifts and evaluating their impact on prediction models are of utmost importance. …”
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A Review of Long-Term Skid Resistance of Asphalt Pavement by Yuanfeng Chen, Zhitang Li, Yuankuo Wang, Guoxi Liang, Xiaolong Yang

“…In this paper, the detection method, decay model, influence factors, and prediction model of the L-TSR of AP are summarized. …”
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