Use of machine learning to predict creativity among nurses: a multidisciplinary approach by Rola H. Mudallal, Majd T. Mrayyan, Mohammad Kharabsheh

“…The developed decision support system may be valuable for helping nurse managers evaluate creativity among nurses; this allows for more informed decisions about staff allocation, development, and resource optimization. Researchers are encouraged to use machine learning models because they achieve good prediction performance with high precision. …”
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Optimized design and performance testing of hydraulic electrostatic actuator by Yuze Ye, Qingsong He, Changli Yang, Xiaodong Xu, Lin Xie, Diyi Liu, Bo Zeng, Zhijian Leng

“…Actuation strain tests were conducted with optimized parameters under no-load. The experimental results of the actuation strain test show that the relative error between the test value and the model prediction value of 16.47% is less than 5%, and the optimization model results are reliable. …”
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Damage prediction of rear plate in Whipple shields based on machine learning method by Chenyang Wu, Xiangbiao Liao, Lvtan Chen, Xiaowei Chen

“…The results demonstrate that the training and prediction accuracies using the Random Forest (RF) algorithm significantly surpass those using Artificial Neural Networks (ANNs) and Support Vector Machine (SVM). The RF-based model effectively identifies damage features in sparsely distributed debris cloud and cumulative effect. …”
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AI and Machine Learning for Precision Medicine in Acute Pancreatitis: A Narrative Review by Sandra López Gordo, Elena Ramirez-Maldonado, Maria Teresa Fernandez-Planas, Ernest Bombuy, Robert Memba, Rosa Jorba

“…This review aims to explore the transformative role of artificial intelligence (AI) and machine learning (ML) in AP management, focusing on their applications in diagnosis, severity prediction, complication management, and treatment optimization. …”
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Machine learning insights into scapular stabilization for alleviating shoulder pain in college students by Omar M. Mabrouk, Doaa A. Abdel Hady, Tarek Abd El-Hafeez

“…The results reveal that scapular stabilization exercises, when optimized using machine learning algorithms, significantly contribute to reducing shoulder pain in college students. …”
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Machine learning approach for Studying the multifunctionality of soil against global climate changes by Xiangng Hu, Yingying Xie, Qixing Zhou, Li Mu

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A Review on Revolutionizing Healthcare Technologies with AI and ML Applications in Pharmaceutical Sciences by Priyanka Kandhare, Mrunal Kurlekar, Tanvi Deshpande, Atmaram Pawar

“…This review explores the diverse applications of AI and ML, emphasizing their role in predictive modeling, drug repurposing, lead optimization, and clinical trials. …”
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RESEARCH ON THE REMAINING INTENSITY OF PIPELINE CORROSION BASED ON IWOA-LSSVM by ZHANG Jia, Ll LinFeng, WANG HaoJie, ZHANG Ting

“…In response to pipeline corrosion surplus intensity, a surplus intensity prediction method based on the Improved Whale Optimization Algorithm (IWOA ) -Least Square Support Vector Machine (LSSVM) combination algorithm model. …”
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Using a graph to schematize the test results of mining dump trucks by Dianov V.A., Bokarev A.I., Kartashov A.B., Dubinkin D.M., Pashkov D.A.

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Machine learning for defect condition rating of wall wooden columns in ancient buildings by Yufeng Li, Wu Ouyang, Zhenbo Xin, Houjiang Zhang, Shuqi Sun, Dian Zhang, Wenbo Zhang

“…The RBF neural network model achieved the highest accuracy (94.57 %) on the feature fusion dataset, while Grey Wolf Optimizer (GWO) optimization further improved accuracy to 96.74 %. …”
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Quantum Computing and Machine Learning in Medical Decision-Making: A Comprehensive Review by James C. L. Chow

“…Meanwhile, ML has already demonstrated significant success in medical imaging, predictive modeling, and decision support. Their convergence, particularly through quantum machine learning (QML), presents opportunities for future advancements in processing high-dimensional healthcare data and improving clinical outcomes. …”
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Research on Fault Diagnosis of Traction Power Supply System Based on PSO-LSSVM by Lei ZHANG

“…According to the working principle and characteristics of the train power supply system, the relationship between the fault phenomenon and the origin was analyzed, and the characteristic signals used for fault diagnosis were extracted. A fault diagnosis model based on PSO optimized least squares support vector machine was established, and PCA algorithm was used to extract data characteristics as input of fault diagnosis model, and reduce input dimension. …”
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Machine learning framework for sustainable traffic management and safety in AlKharj city by Ali Louati

“…We develop predictive models for accident hotspots, adaptive traffic systems, and fuel-efficient routing. …”
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Research on ischemic stroke risk assessment based on CTA radiomics and machine learning by Zhi-Li Li, Hong-Yu Yang, Xiao-Xiao Lv, Ya-Kun Zhang, Xin-Yu Zhu, Yu-Rou Zhang, Li Guo

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The use of acoustic emission technique in MWD for mine to mill approach as a smart tool for sustainable mining by Mohammad Hossein Jalalian, Raheb Bagherpour, Mehrbod Khoshouei

“…This study employed a Support Vector Machine (SVM) model to predict rock mass properties from drilling acoustic signals. …”
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Achieving Equity via Transfer Learning With Fairness Optimization by Xiaoyang Wang, Chia-Hsuan Chang, Christopher C. Yang

“…This paper proposes Transfer Learning with Fairness Optimization (TLFO), a novel framework that serially optimizes predictive performance and fairness in machine learning models. …”
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Advances in Composite Power System Reliability Assessment: Trends and Machine Learning Role by Chiranjeevi Yarramsetty, Tukaram Moger, Debashisha Jena, Veeranki Srinivasa Rao

“…A comparative examination of conventional and Machine Learning (ML)-based methods demonstrates that deep learning models, such as Convolutional Neural Networks, offer substantial reductions in computational time while maintaining reliability assessment precision. …”
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Machine Learning Innovations for Improving Mineral Recovery and Processing: A Comprehensive Review* by Korie, Josephmartin Izuchukwu*, Chudi-Ajabor, Ogochukwu Gabriela, Ezeonyema, Chukwudalu Chukwuekezie, Oshim, Francisca Ogechukwu

“…Among these applications, predictive modeling for process optimization and enhanced ore sorting and classification stand out, with ANN being the most frequently employed algorithm. …”
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SBNNR: Small-Size Bat-Optimized KNN Regression by Rasool Seyghaly, Jordi Garcia, Xavi Masip-Bruin, Jovana Kuljanin

“…On the other hand, researchers are interested in using machine learning methods to analyze this scale of data. …”
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Tracking dustbathing behavior of cage-free laying hens with machine vision technologies by Bidur Paneru, Ramesh Bist, Xiao Yang, Lilong Chai

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