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

“…However, implementation must also address challenges related to health equity, algorithmic bias, and system integration. As precision medicine continues to evolve, it holds the promise of optimizing early detection, minimizing harm, and extending the benefits of lung cancer screening to broader and more diverse populations. …”
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Wireless positioning methods for mitigating the influence of environmental and terminal diversity by Jietai WANG, Youlian GUAN, Xiaoniu YANG, Zhenxing LUO, Jianbiao YU

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Machine Learning-Driven Prediction of One-Year Readmission in HFrEF Patients: The Key Role of Inflammation by Ma F, Hu Y, Han P, Qiu Y, Liu Y, Ren J

“…Seven machine learning (ML) algorithms were trained and validated using a 7:3 dataset split; the metrics of the model included the area under the curve (AUC), accuracy, sensitivity, specificity, F1 score, and Brier score. …”
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Towards Robust Speech Models: Mitigating Backdoor Attacks via Audio Signal Enhancement and Fine-Pruning Techniques by Heyan Sun, Qi Zhong, Minfeng Qi, Uno Fang, Guoyi Shi, Sanshuai Cui

“…Second, we apply an adaptive fine-pruning algorithm to selectively deactivate malicious neurons while preserving the model’s linguistic capabilities. …”
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Research on the Influence of Composite Modification Design on Tooth Surface Wear of Transmission Gears by Bai Xiaoning, Li Yonghua, Wang Denglong, Zhang Dongxu

“…Moreover, the sparrow search algorithm (SSA) improved by the Sine chaotic mapping is used to optimize the back propagation (BP) neural network, and the accuracy of Sine-SSA-BP is verified by comparing it with the traditional BP, so as to characterize the implicit relationship between the modification parameters and the gear wear. …”
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RBCKF-Based Vehicle State Estimation by Adaptive Weighted Fusion Strategy Considering Composite-State Tire Model by Xi Chen, Xinlong Cheng

“…Meanwhile, considering the adaptive and dynamic adjustment capabilities of the observation system in complex state-change scenarios, an estimation strategy based on adaptive weight fusion and a model-based estimator is proposed. The results confirm that the robust bias compensation Kalman filter can ensure estimation exactitude and robustness when the vehicle state fluctuates greatly, and the proposed fusion strategy can ensure that the vehicle maintains optimal estimation performance during operating condition switching.…”
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Integrating Learning-Driven Model Behavior and Data Representation for Enhanced Remaining Useful Life Prediction in Rotating Machinery by Tarek Berghout, Eric Bechhoefer, Faycal Djeffal, Wei Hong Lim

“…Both RF and RexNet undergo hyperparameter optimization using Bayesian methods under variability reduction (i.e., standard deviation) of residuals, allowing the algorithms to reach optimal solutions and enabling fair comparisons with state-of-the-art approaches. …”
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Fast fault diagnosis of smart grid equipment based on deep neural network model based on knowledge graph. by Lin Jun, Zhou Chenliang

“…It can not only meet the demand of users and realize the optimal allocation of resources, but also improve the safety, economy and reliability of power supply, it has become a major trend in the future development of electric power industry. …”
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A Novel Approach to Efficiently Verify Sequential Consistency in Concurrent Programs by Mohammed H. Abdulwahhab, Parosh Aziz Abdulla, Karwan Jacksi

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SPARCQ: Enhancing Scalability and Adaptability of Proactive Edge Caching Through Q-Learning by Shruti Lall, Johan de Clercq, Nelishia Pillay, Bodhaswar T. Maharaj

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No-load and on-load performance analysis of 10-stator-slots five phase flux switching machines with non-overlapped winding configurations by Muhammad Yousuf, Faisal Khan, Ahmed Tameemi, Wasiq Ullah

“…An evolutionary optimization process based on the genetic algorithm (GA) integrated with the JMAG software is executed to optimize the machine models, resulting in significant improvements in the analyzed WFFS machine models. …”
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Application of Machine Learning for Adaptive Trajectory Control of UAVs Under Uncertainty by Alexander S. Ermilov, Olga A. Saltykova

“…Special attention is given to the practical application of ML for environmental change prediction and flight trajectory optimization. Examples of real-world ML algorithm implementations include successful developments by Russian and foreign companies, demonstrating high levels of autonomy and adaptive control. …”
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Research on High Arch Dam Deformation Monitoring Model with Deep Capturing Related Features in Factor-time Dimensions by XUE Jianghan, ZHANG Pengtao, TIAN Jichen, LU Xiang, CHEN Jiankang, Guo Yinju

“…However, at the present stage, the dam prediction model based on machine learning mostly adopts the means of data preprocessing, using optimization algorithm, and using the model's characteristics to stack multiple models, lacking in in-depth consideration of the physical mechanism of dam deformation. …”
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A study on monthly sales forecasting of new energy vehicles in urban areas using the WOA-BiGRU model. by Xiangtu Li

“…To accurately predict the sales of new energy vehicles (NEVs) in Chinese cities and explore the applicability of optimization algorithms for GRU models in forecasting urban NEV sales., this paper conducts a spatiotemporal analysis of urban NEV sales data. …”
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Enhancing Daylight and Energy Efficiency in Hot Climate Regions with a Perforated Shading System Using a Hybrid Approach Considering Different Case Studies by Basma Gaber, Changhong Zhan, Xueying Han, Mohamed Omar, Guanghao Li

“…A hybrid approach integrating parametric modeling, machine learning, multi-criteria decision-making (MCDM), and genetic algorithm (GA) is used to optimize the design incorporating architects’ preferences. …”
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Advanced biomedical imaging for identifying blood cell type: Integrating segmentation, feature extraction, and GraphSAGE model by Nur Mohammad Fahad, Mohaimenul Azam Khan Raiaan, Arefin Ittesafun Abian, Ripon Kumar Debnath, Sidratul Montaha, Mirjam Jonkman, Sami Azam

“…An improved GraphSAGE model is constructed to classify blood cells. …”
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Large Language Model and Digital Twins Empowered Asynchronous Federated Learning for Secure Data Sharing in Intelligent Labeling by Xuanzhu Sheng, Chao Yu, Xiaolong Cui, Yang Zhou

“…By analysising and comparing and with other existing asynchronous federated learning algorithms, the experimental results show that our proposed method outperforms other algorithms in terms of performance, such as model accuracy and running time. …”
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The role of artificial intelligence in vascular care by Nehaar Nimmagadda, BS, Edouard Aboian, MD, Sharon Kiang, MD, Uwe Fischer, MD

“…The review also explores cost-effectiveness data, resource optimization, and challenges such as algorithmic bias and data privacy. …”
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Intelligent Methods of Operational Response to Accidents in Urban Water Supply Systems Based on LSTM Neural Network Models by Aliaksey A. Kapanski, Nadezeya V. Hruntovich, Roman V. Klyuev, Aleksandr E. Boltrushevich, Svetlana N. Sorokova, Egor A. Efremenkov, Anton Y. Demin, Nikita V. Martyushev

“…The results obtained demonstrate that the optimal model consists of two LSTM layers, one Dropout layer, and one Dense layer. …”
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A novel voting ensemble model empowered by metaheuristic feature selection for accurate flash flood susceptibility mapping by Radhwan A. Saleh, Ahmed M. Al-Areeq, Amran A. Al Aghbari, Mustafa Ghaleb, Mohammed Benaafi, Nabil M. Al‑Areeq, Baqer M. Al-Ramadan

“…Through comprehensive comparisons with established algorithms such as the Artificial Bee Colony (ABC) and Gray Wolf Optimizer (GWO), MSA refined the selection, identifying 'elevation’ and 'distance to streams’ as optimal factors. …”
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