Machine Learning Unveils the Impacts of Key Elements and Their Interaction on the Ambient-Temperature Tensile Properties of Cast Titanium Aluminides Employing SHAP Analysis by Shiqiu Liu, Li Liang

“…Comparative analysis of three algorithms within the training dataset proved the random forest regression (RFR) as the optimal modeling approach. …”
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The Role of Artificial Intelligence in Aviation Construction Projects in the United Arab Emirates: Insights from Construction Professionals by Mariam Abdalla Alketbi, Fikri Dweiri, Doraid Dalalah

“…The majority agreed that AI has the potential to revolutionize project management processes, improving decision-making, and efficiency. AI tools can predict delays, optimize workflows, and enhance safety through real-time data analytics and machine learning algorithms, reducing risks and human error. …”
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A Data-Driven Comparative Analysis of Machine-Learning Models for Familial Hypercholesterolemia Detection by Tomasz Kocejko

“…This study presents an assessment of familial hypercholesterolemia (FH) probability using different algorithms (CatBoost, XGBoost, Random Forest, SVM) and its ensembles, leveraging electronic health record data. …”
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Assessing the Impact of Mixed Pixel Proportion Training Data on SVM-Based Remote Sensing Classification: A Simulated Study by Jianyu Gu, Russell G. Congalton

“…Support vector machine (SVM) algorithms have been widely utilized in the remote sensing community due to their high performance with small training datasets. …”
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Comparative Analysis of Machine Learning Models for Predicting Innovation Outcomes: An Applied AI Approach by Marko Martinović, Kristian Dokic, Dalibor Pudić

“…The results showed that tree-based boosting algorithms consistently outperformed other models in accuracy, precision, F1-score, and ROC-AUC, while the kernel-based approach excelled in recall. …”
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From Misinformation to Insight: Machine Learning Strategies for Fake News Detection by Despoina Mouratidis, Andreas Kanavos, Katia Kermanidis

“…Our approach systematically compares traditional machine learning classifiers (Naïve Bayes, SVMs, Random Forest) with state-of-the-art deep learning models, such as CNNs, LSTMs, and BERT, while incorporating optimized vectorization techniques, including TF-IDF, Word2Vec, and contextual embeddings. …”
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Linguistic Markers of Pain Communication on X (Formerly Twitter) in US States With High and Low Opioid Mortality: Machine Learning and Semantic Network Analysis by ShinYe Kim, Winson Fu Zun Yang, Zishan Jiwani, Emily Hamm, Shreya Singh

“…Semantic network analysis revealed denser discourse in HDS (density=0.28) focused on distress and barriers to care, while LDS discourse emphasized recovery and optimism. …”
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Deep Temporal Clustering of Pathological Gait Patterns in Post-Stroke Patients Using Joint Angle Trajectories: A Cross-Sectional Study by Gyeongmin Kim, Hyungtai Kim, Yun-Hee Kim, Seung-Jong Kim, Mun-Taek Choi

“…Through this method, six optimal clusters were selected with a silhouette score of 0.2831, which is a relatively higher value compared to other clustering algorithms. …”
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A CART-Based Model for Analyzing the Shear Behaviors of Frozen–Thawed Silty Clay and Structure Interface by Fengpan Zhu, Bo Wang, Zhiqiang Liu

“…This study employs integrated machine learning algorithms to model the shear behavior of frozen–thawed silty clay and the structure interface. …”
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Multi-Fidelity Machine Learning for Identifying Thermal Insulation Integrity of Liquefied Natural Gas Storage Tanks by Wei Lin, Meitao Zou, Mingrui Zhao, Jiaqi Chang, Xiongyao Xie

“…Three machine learning algorithms—Multilayer Perceptron, Random Forest, and Extreme Gradient Boosting—were evaluated to determine the optimal implementation. …”
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The synergy of neuromarketing and artificial intelligence: A comprehensive literature review in the last decade by Ahmed H. Alsharif, Junhai Wang, Salmi Mohd Isa, Nor Zafir Md Salleh, Husam Azzawi Dawas, Mohammed H. Alsharif

“…Emotion, attention, and memory have become vital in NM and AI studies. AI algorithms analyze vast neural and physiological datasets, offering marketers insights into the emotional impact of campaigns, granular insights into consumer focus, and optimizing content for maximum impact. …”
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Precision Medicine in Lung Cancer Screening: A Paradigm Shift in Early Detection—Precision Screening for Lung Cancer by Hsin-Hung Chen, Yun-Ju Wu, Fu-Zong Wu

“…Lung cancer remains the leading cause of cancer-related mortality globally, largely due to late-stage diagnoses. While low-dose computed tomography (LDCT) has improved early detection and reduced mortality in high-risk populations, traditional screening strategies often adopt a one-size-fits-all approach based primarily on age and smoking history. …”
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A Novel Ensemble of Deep Learning Approach for Cybersecurity Intrusion Detection with Explainable Artificial Intelligence by Abdullah Alabdulatif

“…The proposed model combines an Artificial Neural Network and Support Vector Machine as base classifiers and employs a Random Forest as a meta-classifier to fuse predictions, improving detection performance. Recursive Feature Elimination is utilized for optimal feature selection, while SHapley Additive exPlanations (SHAP) provide both global and local interpretability of the model’s decisions. …”
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Automated Microservices Identification Through Business Process Analysis: A Semantic-Driven Clustering Approach by Idris Oumoussa, Rajaa Saidi

“…This work marks a step forward in optimizing system modularity and provides a foundation for future scalability improvements.…”
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Prediction of Myocardial Infarction Based on Non-ECG Sleep Data Combined With Domain Knowledge by Changyun Li, Yonghan Zhao, Qihui Mo, Zhibing Wang, Xi Xu

“…The experiments demonstrate that the model’s accuracy reaches its optimal level by combining the age rule, improving to 73.1%. …”
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Monitoring of vegetation chlorophyll content in photovoltaic areas using UAV-mounted multispectral imaging by Ming Li, Weiyi Wang, Haoran Li, Zekun Yang, Jianjun Li

“…Moreover, the fusion of vegetation indices and texture features effectively improved the accuracy of chlorophyll inversion models; among the six regression algorithms tested, the multilayer perceptron model achieved the highest performance (R² = 0.874, RMSE = 3.725, MAPE = 3.982%). …”
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A Novel Time Delay Nonsingular Fast Terminal Sliding Mode Control for Robot Manipulators with Input Saturation by Thanh Nguyen Truong, Anh Tuan Vo, Hee-Jun Kang

“…Manipulator systems are increasingly deployed across various industries to perform complex, repetitive, and hazardous tasks, necessitating high-precision control for optimal performance. However, the design of effective control algorithms is challenged by nonlinearities, uncertain dynamics, disturbances, and varying real-world conditions. …”
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Personal health data protection and intelligent healthcare applications under generative adversarial network by Xiaoyuan Gao, Wei Mi, Xirui Feng

“…The proposed method employs a multi-generator architecture and optimizes generator parameters through gradient clipping and genetic algorithms, enhancing data privacy protection and the quality and utility of the generated data. …”
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Applications of artificial intelligence in neurosurgical education: a scoping review by Hector Julio Piñera-Castro, Christian Borges-García

“…Abstract Background Artificial intelligence (AI) has transformed medical education through optimized instruction, competency assessment, and personalized learning. …”
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Intelligent gear decision method for vehicle automatic transmission system based on data mining by Yong Wang, Jianfeng Zeng, Pengfei Du, Huachao Xu

“…Subsequently, dynamic programming algorithms are employed to optimize intelligent gear decisions. …”
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