Development and Validation of a Machine Learning Model for Early Prediction of Sepsis Onset in Hospital Inpatients from All Departments by Pierre-Elliott Thiboud, Quentin François, Cécile Faure, Gilles Chaufferin, Barthélémy Arribe, Nicolas Ettahar

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Developing predictive models for tocilizumab response in rheumatoid arthritis: a gene expression and machine learning approaches by Weiya Lan, Wei Du, Wukai Ma, Xueming Yao, Zong Jiang, Jing Zhou, Changming Chen, Chunxia Wang, Fang Tang

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Prediction of IPO performance from prospectus using multinomial logistic regression, a machine learning model by Mazin Fahad Alahmadi, Mustafa Tahsin Yilmaz

“…The MLR model had a higher level of accuracy when compared with other machine learning algorithms. By using the model developed here, investors can improve their ability to predict the direction of the return on their investment in an IPO, at least for the first month. …”
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The Local Path Planning Algorithm for Amphibious Robots Based on an Improved Dynamic Window Approach by Xiaoqiang Dai, Chengye Liu, Qiang Lai, Xin Huang, Qingjun Zeng, Ming Liu

“…The speed resolution adaptive adjustment algorithm improves the ability to pass through a complex multiple-obstacle area, and the dynamic obstacle prediction algorithm optimizes obstacle avoidance paths. …”
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Optimized ANN Model for Predicting Buckling Strength of Metallic Aerospace Panels Under Compressive Loading by Shahrukh Khan, Saiaf Bin Rayhan, Md Mazedur Rahman, Jakiya Sultana, Gyula Varga

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Leveraging Machine Learning for Exchange Rate Prediction: A Business and Financial Management Perspective in Nigeria by Adedeji Daniel Gbadebo

“…Methodology The paper employs Logistic Linear Regression, Support Vector Machine, Random Forest, and XGBoost algorithms to predict the univariate time series of Nigeria's exchange rate against the US dollar, using both hourly and daily data. …”
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Adaptive Variational Modal Decomposition–Dual Attention Mechanism Parallel Residual Network: A Tool Lifetime Prediction Method Based on Adaptive Noise Reduction by Jing Kang, Taiyong Wang, Yi Li, Ye Wei, Yaomin Zhang, Ying Tian

“…The method first adapts the parameters of the variational modal noise reduction algorithm using an improved sparrow optimization algorithm, and then reconstructs the original vibration signal with noise reduction. …”
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Development of Digital Twin for FDM Printer With Preventive Cyber-Attack and Control Algorithms by Md Hazrat Ali, Asad Waqar Malik, Nursultan Jyeniskhan, Muhammad Arif Mahmood, Essam Shehab, Frank Liou

“…It also highlights a model predictive control (MPC) algorithm based on a real-time feedback system for controlling the material feed. …”
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A multi-objective optimization-based ensemble neural network wind speed prediction model by Haoyuan Ma, Chang Liu, Ziyuan Qiao, Yuan Liang, Hongqing Wang

Subjects: “…Wind speed prediction…”
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A Noise Reduction Method for Photoacoustic Imaging <italic>In Vivo</italic> Based on EMD and Conditional Mutual Information by Meng Zhou, Haibo Xia, Hongtao Zhong, Jiayao Zhang, Fei Gao

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Deep Learning Models for Reference Evapotranspiration Prediction in Bangladesh by Abul Kashem, Pobithra Das, Uaktho Baishnab

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Maximizing influence via link prediction in evolving networks by Kexin Zhang, Mo Li, Shuang Teng, Lingling Li, Yi Wang, Xuezhuan Zhao, Jinhong Di, Ji Zhang

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Mobile application based on KDD to predict high-crime areas and promote sustainability in citizen security in a district of Lima-Perú by Hugo Vega-Huerta, Javier Vilca Velasquez, Nicolas Anicama Espinoza, Gisella Luisa Elena Maquen-Niño, Luis Guerra-Grados, Jorge Pantoja-Collantes, Oscar Benito-Pacheco, Juan Carlos Lázaro-Guillermo, Adegundo Camara-Figueroa, Javier Cabrera-Díaz, Rubén Gil-Calvo, Frida López-Córdova

“…The data mining process follows the KDD methodology, which includes the stages of selection, preprocessing, transformation, data mining, evaluation and knowledge consolidation. Machine learning algorithms, such as Random Forest and Gradient Boosting, were used to make these predictions. …”
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Development of a Secured IoT-Based Flood Monitoring and Forecasting System Using Genetic-Algorithm-Based Neuro-Fuzzy Network by Hero Rafael Castillo Arante, Edwin Sybingco, Maria Antonette Roque, Leonard Ambata, Alvin Chua, Alvin Neil Gutierrez

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Predicting Live Weight for Female Rabbits of Meat Crosses From Body Measurements Using LightGBM, XGBoost and Support Vector Machine Algorithms by Hasan Önder, Cem Tirink, Taras Yakubets, Andriy Getya, Mykhalio Matvieiev, Ruslan Kononenko, Uğur Şen, Çağri Özgür Özkan, Tolga Tolun, Fahrettin Kaya

“…A highly efficient gradient‐boosting decision tree (LightGBM), eXtreme gradient‐boosting (XGBoost) and support vector machine (SVM) algorithms were evaluated and compared to the prediction of BW. …”
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Enhanced mother optimization algorithm-based optimal reconfiguration to accommodate emerging electric vehicle demand by Radha Rani K., Sobha Rani P., Swarnasri K., Varaprasad Janamala

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The impact of intravenous iodinated contrast agents on radiotherapy dose calculation and radiobiological effect predictions in central lung cancer by Defu Yang, Feng Shang, Ying Xu, Ying Yan

“…This study evaluates and compares dosimetric differences and predictions of Tumor Control Probability (TCP) and Normal Tissue Complication Probability (NTCP) between the Analytic Anisotropic Algorithm (AAA) and Acuros XB (AXB) algorithm in lung cancer radiotherapy, under both contrast-enhanced and non-contrast enhanced CT conditions.MethodsTwenty patients with centralized lung cancer treated with intensity-modulated radiation therapy (IMRT) technique, including two patients with small cell lung cancer and 18 with non-small cell lung cancer, were selected to undergo CT scanning with and without contrast. …”
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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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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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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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