Predicting emergency department admissions using a machine-learning algorithm: a proof of concept with retrospective study by Cyrielle Brossard, Christophe Goetz, Pierre Catoire, Lauriane Cipolat, Christophe Guyeux, Cédric Gil Jardine, Mahuna Akplogan, Laure Abensur Vuillaume

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Multi-domain Urdu fake news detection using pre-trained ensemble model by Sheetal Harris, Hassan Jalil Hadi, Naveed Ahmad, Mohammed Ali Alshara

“…Furthermore, limited research in resource-constrained languages has created language bias in Artificial Intelligence (AI) research, which is concentrated in this study. …”
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Investigation of the Wear Behavior of AA6063/Zirconium Oxide Nanocomposites Using Hybrid Machine Learning Algorithms by R. Reena Roy, Leninisha Shanmugam, A. Vinothini, Nirmala Venkatachalam, G. Sumathy, Bhavadharini Murugeshan, P. Mercy Rajaselvi Beaulah, Gizachew Assefa Kerga

“…This research created hot-pressed composites of the AA6063 matrix with varying concentrations of ZrO2 (0.25, 0.5, and 1 wt %). …”
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Machine learning discovery of the dielectric properties of strontium-containing condensed matter by Dongyang Huang, Jiaxing Fu, Chenghao Yu

“…The pursuit of materials with high dielectric constants has long been a central focus in both fundamental research and practical applications. Traditional theoretical predictions or first-principles calculations of dielectric constants are often challenging and require significant time and computational resources. …”
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Transformer–BiLSTM Fusion Neural Network for Short-Term PV Output Prediction Based on NRBO Algorithm and VMD by Xiaowei Fan, Ruimiao Wang, Yi Yang, Jingang Wang

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Wind power generation prediction using LSTM model optimized by sparrow search algorithm and firefly algorithm by Wenjing Zhang, Hongjing Yan, Lili Xiang, Linling Shao

“…Then, the sparrow search algorithm and firefly algorithm are combined to optimize the hyperparameter configuration, improving the predictive performance and global search ability of the model. …”
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Audio Feature Space Analysis for Emotion Recognition from Spoken Sentences by Lukasz SMIETANKA, Tomasz MAKA

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Enhancing convergence speed with feature enforcing physics-informed neural networks using boundary conditions as prior knowledge by Mahyar Jahani-nasab, Mohamad Ali Bijarchi

“…Abstract This research introduces an accelerated training approach for Vanilla Physics-Informed Neural Networks (PINNs) that addresses three factors affecting the loss function: the initial weight state of the neural network, the ratio of domain to boundary points, and the loss weighting factor. …”
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Drosophila Eye Gene Regulatory Network Inference Using BioGRNsemble: An Ensemble-of-Ensembles Machine Learning Approach by Abdul Jawad Mohammed, Amal Khalifa

“…Advances in bioinformatics, driven by genomic data and machine learning, have significantly expanded GRN research, enabling deeper insights into these interactions. …”
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Efficient lung cancer detection using computational intelligence and ensemble learning. by Richa Jain, Parminder Singh, Mohamed Abdelkader, Wadii Boulila

“…In this research, we aim to develop an ecologically considerate lung cancer therapy prototype model that maximizes resource utilization by leveraging recent advancements in computational intelligence. …”
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Enhancing Software Sustainability: Leveraging Large Language Models to Evaluate Security Requirements Fulfillment in Requirements Engineering by Ahmad F. Subahi

“…In the digital era, cybersecurity is integral for preserving national security, digital privacy, and social sustainability. This research emphasizes the role of non-functional equirements (NFRs) in developing secure software systems that enhance societal wellbeing by ensuring data protection, user privacy, and system robustness. …”
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Performance Evaluation of Neighbors-Based Learning Methods for Network Intrusion Detection System by Ngoc Thien Nguyen

“…Consequently, intrusion detection technologies are being actively researched and optimized to enhance threat detection and prevention capabilities. …”
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Stroke Risk Classification Using the Ensemble Learning Method of XGBoost and Random Forest by Gullam Almuzadid, Egia Rosi Subhiyakto

“…The proposed approach significantly improved predictive accuracy compared to previous research, demonstrating the effectiveness of ensemble learning and preprocessing methods in developing reliable, high-performing machine learning models for early stroke risk assessment.…”
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A survey on multi-agent reinforcement learning and its application by Zepeng Ning, Lihua Xie

“…We also address critical operational aspects, such as hyperparameter tuning and computational complexity, which are pivotal in practical implementations of MARL. …”
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Talent identification in soccer using a one-class support vector machine by Jauhiainen S., Äyrämö S., Forsman H., Kauppi J-P.

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AI-Assisted Game Theory Approaches to Bid Pricing Under Uncertainty in Construction by Joas Serugga

“…AI can classify conservative (70%) and aggressive (30%) bidders through analysis, demonstrating the potential of this integrated approach to improve bid accuracy (cost estimates are generally within 10% of actual bid prices), optimise risk-sharing strategies, and enhance decision making in dynamic and competitive environments. The research extends the current body of knowledge with its potential to reshape bid-pricing strategies in construction in an integrated AI–game-theoretic model under uncertainty.…”
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Using Machine Learning on Macroeconomic, Technical, and Sentiment Indicators for Stock Market Forecasting by Michalis Patsiarikas, George Papageorgiou, Christos Tjortjis

“…Financial forecasting is a research and practical challenge, providing meaningful economic and strategic insights. …”
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An In-Depth Look at Rising Temperatures: Forecasting with Advanced Time Series Models in Major US Regions by Kameron B. Kinast, Ernest Fokoué

“…Our analysis includes hyperparameter optimization for each model to ensure peak performance. …”
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Optimized hybrid deep learning for cross-linguistic sentiment analysis: a novel approach by Vipin Jain, Lokesh Malviya, Anjana .S

“…Abstract Sentiment analysis, the process of extracting and classifying opinions expressed in text, has gained significant traction in different fields, such as market research, customer feedback, and social media analysis. …”
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Prediction of Freezing Time During Hydrogen Fueling Using Machine Learning by Ji-Ah Choi, Ji-Seong Jang, Sang-Won Ji

“…Hyperparameter optimization was performed using random search to enhance model performance. …”
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