Application of Battery Life Prediction Technology in EMUs by DAI Yi, YU Tianjian, CHENG Shu, WU Xun, LIU Jiawen

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Exploring machine learning algorithms to predict short birth intervals and identify its determinants among reproductive-age women in East Africa by Tirualem Zeleke Yehuala, Bezawit Melak Fente, Sisay Maru Wubante

“…Method This study employs machine learning algorithms to predict short birth intervals among reproductive-age women in East Africa, using a dataset from Demographic and Health Surveys. …”
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Exploration of Machine Learning Models for Prediction of Gene Electrotransfer Treatment Outcomes by Alex Otten, Michael Francis, Anna Bulysheva

“…This study elucidates areas where predictive ML algorithms may ideally inform GET study design to accelerate optimization and improve efficiencies upon the further training of these models.…”
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Nomogram for predicting the severity of high-risk plaques in acute coronary syndrome by Miao-Na Bai, Miao-Na Bai, Miao-Na Bai, Ji-Xiang Wang, Ji-Xiang Wang, Xiao-Wei Li, Xiao-Wei Li, Xiao-Wei Li, Jing-Xian Wang, Jing-Xian Wang, Yu-Hang Wang, Yu-Hang Wang, Yin Liu, Yin Liu, Yin Liu, Jing Gao, Jing Gao, Jing Gao, Jing Gao

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Enhancing stock market predictions for classifying unlabelled celebrities' twitter data by Baljinder Singh, Mandeep Kaur, Gurbinder Singh Brar, NZ Jhanjhi

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Research on the Performance of Vehicle Lateral Control Algorithm Based on Vehicle Speed Variation by Weihai Zhang, Jinbo Wang, Tongjia Pang

Subjects: “…model predictive control algorithm…”
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Machine learning algorithms for risk factor selection with application to 60-day sepsis morbidity risk for a geriatric hip fracture cohort by Zhe Xu, Ruguo Zhang, Qiuhan Chen, Guoxuan Peng, Shanpeng Luo, Chen Liu, Ling Zeng, Jin Deng

“…The purpose of this study was to screen for risk factors for 60-day sepsis morbidity after hip fracture and to establish a predictive model using various machine learning algorithms. …”
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A Prediction Model of Stable Warfarin Doses in Patients After Mechanical Heart Valve Replacement Based on a Machine Learning Algorithm by Bowen Guo, Cong Chen, Junhang Jia, Jubing Zheng, Yue Song, Taoshuai Liu, Kui Zhang, Yang Li, Ran Dong

“…The performance of these algorithms was evaluated and compared using R-squared (R2), mean absolute error (MAE), and ideal prediction percentage to identify the optimal algorithm for predicting the stable warfarin dose and verify its clinical significance. …”
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Optimising islanded AC microgrid control: A hierarchical approach with FCS-VMPC and consensus algorithm by Zawar Khan, Muhammad Aamir, Rizwanullah Khan, Mohd Fairouz Mohd Yousof

Subjects: “…Consensus algorithm…”
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Multi-step Prediction of Monthly Sediment Concentration Based on WPT-ARO-DBN/WPT-EPO-DBN Model by GAO Xuemei, CUI Dongwen

Subjects: “…prediction of monthly sediment concentration…”
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Performance Analysis of Diabetes Detection Using Machine Learning Classifiers by Hung Huynh, Liu Hui, Ngoc Han Nguyen, Ruixuan Qiao

Subjects: “…diabetes prediction and diagnosis, machine learning, classifiers, algorithms.…”
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Research on the Time-varying Meshing Stiffness Algorithm of Spur Gears with Large Tooth Number Cracks by Jiao Wei, Xu Kejun, Qin Haiqin

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Wireless Channel Prediction Using Artificial Intelligence With Imperfect Datasets by Gowhar Javanmardi, Ramiro Samano Robles

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Multiscale Feature Modeling and Interpretability Analysis of the SHAP Method for Predicting the Lifespan of Landslide Dams by Zhengze Huang, Yuqi Bai, Hengyu Liu, Yun Lin

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A solving new method for the urea-selective catalytic reduction (SCR) system in a diesel engine using coupled hyperbolic-parabolic partial differential equations (PDEs) by Wenlong Liu, Ying Gao, Yuelin You, Changwen Jiang, Taoyi Hua, Bocong Xia

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Construction of a risk prediction model for postoperative deep vein thrombosis in colorectal cancer patients based on machine learning algorithms by Xin Liu, Xingming Shu, Yejiang Zhou, Yifan Jiang

“…Moreover, the SHAP method identified age and preoperative prealbumin as the primary determinants influencing ML model predictions. Finally, the study employed LIME for more precise prediction and interpretation of individual predictions.ConclusionThe machine learning algorithms effectively predicted postoperative lower limb deep vein thrombosis in colorectal cancer patients. …”
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Development and Internal Validation of Machine Learning Algorithms for Predicting Subsequent Contralateral Slipped Capital Femoral Epiphysis in Patients With Unilateral Slips by David P. VanEenenaam, Jr., BS, Carter Hall, BS, Daniel A. Maranho, MD, PhD, Christopher J. DeFrancesco, MD, Eduardo N. Novais, MD, Wudbhav N. Sankar, MD

“…Machine learning (ML) algorithms can be leveraged to identify complex, nonlinear patterns in data and allow for more accurate predictions on which patients may need a prophylactic pin. …”
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Trustworthy Load Prediction for Cantilever Roadheader Robot Without Imputation by Pengjiang Wang, Yuxin Li, Yunwang Li, Yang Shen, Weixiong Zheng, Shigen Fu

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Short-Term Wind Power Prediction Model Based on PSO-CNN-LSTM by Qingquan Lv, Jialin Zhang, Jianmei Zhang, Zhenzhen Zhang, Qiang Zhou, Pengfei Gao, Haozhe Zhang

“…The predictive performance of the proposed PSO-CNN-LSTM hybrid algorithm is evaluated against benchmark models using four statistical metrics: RMSE, MAE, MSE, and R². …”
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Explainable machine learning reveals ribosome biogenesis biomarkers in preeclampsia risk prediction by Jingjing Chen, Dan Zhang, Chengxiu Zhu, Lin Lin, Kejun Ye, Ying Hua, Mengjia Peng

“…Functional enrichment analyses delineated the dysregulation of pathways, while weighted gene co-expression network analysis identified hub genes within ribosome biogenesis-associated modules. A multi-algorithm machine learning framework was employed to optimize predictive performance, with model interpretability achieved through SHapley Additive exPlanations and diagnostic accuracy validated by receiver operating characteristic curves. …”
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