Artificial Intelligence Empowers Solid-State Batteries for Material Screening and Performance Evaluation by Sheng Wang, Jincheng Liu, Xiaopan Song, Huajian Xu, Yang Gu, Junyu Fan, Bin Sun, Linwei Yu

“…The achievements of various ML algorithms in predicting different performances of the battery management system are discussed. …”
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An Approach Based on the Use of Commercial Codes and Engineering Judgement for the Battle of Water Demand Forecasting by Alfredo Iglesias-Rey, Carlos Alfonso López Hojas, F. Javier Martínez-Solano, Pedro L. Iglesias-Rey

“…Initial data filtering, input variable determination, and simultaneous application of RNN, LSTM, and GRU forecasting algorithms are conducted. Results are evaluated based on Battle of Water Demand Forecasting criteria, refining parameters iteratively for enhanced prediction accuracy. …”
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Heart failure and atrial fibrillation: updates and perspectives by V. N. Larina, I. K. Skiba, A. S. Skiba, V. G. Larin, E. A. Vartanyan

“…The article discusses modern approaches and features of management, as well as predicting the risk of complications in patients with cardiac arrhythmias, in particular, atrial fibrillation, and the potential of using conservative and interventional treatment methods for heart failure (HF), taking into account updates and achievements in clinical practice. …”
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An interpretable machine learning-assisted diagnostic model for Kawasaki disease in children by Mengyu Duan, Zhimin Geng, Lichao Gao, Yonggen Zhao, Zheming Li, Lindong Chen, Pekka Kuosmanen, Guoqiang Qi, Fangqi Gong, Gang Yu

“…Furthermore, its interpretability enhances model transparency, facilitating clinicians’ understanding of prediction reliability.…”
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Optimal fusion β-quaternion filtering from delayed observations and packet losses with compensation strategy under properness by J. D. Jiménez-López, R. M. Fernández-Alcalá, F. Gutiérrez-Trujillo, E. Grassucci, D. Comminiello

“…A numerical example is presented to illustrate, among other aspects, the substantial reduction in computational time achieved by the proposed algorithm, as well as its superior estimation accuracy compared to conventional quaternion processing methods.…”
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Exploring Gender Differences in Fatwa through Machine Learning by Emad Mohamed, Raheem Sarwar

“…Our methodology involves comprehensive experimental analysis, utilizing advanced Arabic text preprocessing alongside machine learning algorithms. We concentrate on two primary objectives: predicting the gender of the questioner and forecasting the popularity of answers. …”
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Practical aspects of forecasting the company’s financial performance by V. V. Kookueva, A. A. Aliev, R. I. Khavich

“…The article considers the methodological problems of forecasting key financial indicators related to forecasting the final results of the company. The algorithm for creating refined factor predictive models of financial indicators has been presented and tested. …”
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Determining Functional Safety Indices of CWR Track Subject to Action of Thermal Compression Forces by O. A. Suslov

“…In the present paper there is proposed failure probability assessment algorithm based on the thermal track buckling emergence criterion. …”
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Trabecular bone score in rheumatic disease by M. V. Kozyreva, O. A. Nikitinskaya, N. V. Toroptsova

“…The data obtained indicate that TBS predicts fractures better in RD, especially in patients receiving glucocorticoids, than BMD or the FRAX algorithm. …”
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An Information Granulated Based SVM Approach for Anomaly Detection of Main Transformers in Nuclear Power Plants by Wenmin Yu, Ren Yu, Cheng Li

“…This study introduces a framework for main transformer predictive-based maintenance management. A condition prediction method based on the online support vector machine (SVM) regression model is proposed, with the input data being preprocessed using the information granulation method, and the parameters of the model are optimized using the particle swarm optimization (PSO) algorithm. …”
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The Transformative Impact of Artificial Intelligence in Healthcare: Innovations, applications, and future prospects by Shen Ruoyu

“…This study discusses the transformative applications of AI in healthcare, including how technologies such as machine learning, neural networks, deep learning, and natural language processing can be used for diagnosis, personalized medicine, predictive analytics, virtual health assistants, surgery, and rehabilitation. …”
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Residual XGBoost regression-Based individual moving range control chart for Gross Domestic Product growth monitoring. by Rahida Rihhadatul Aisy, Latifatuz Zulfa, Yolanda Rahim, Muhammad Ahsan

“…By effectively capturing complex nonlinear relationships and mitigating autocorrelation, the proposed model offers enhanced predictive accuracy compared to conventional methods. …”
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Artificial intelligence-assisted method of structural health monitoring of subway shield tunnel based on insulation degradation location. by Yiwei Zhao, Chengtao Wang, Yi Tao

“…The present study is dedicated to develop an integrated network-based method for locating the insulation degradation in subway tunnel. In this work, a predictive model based on LWQPSO-SOM algorithm is designed to cluster the risk level of stray current leakage through data mining. …”
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Exploring Artificial Intelligence for Enhanced Endodontic Practice: Applications, Challenges, and Future Directions by Santosh R. Patil, Mohmed Isaqali Karobari

“…However, challenges such as data privacy issues, algorithmic biases, and integration barriers must be addressed to enable broader adoption. …”
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Research on the Performance Optimization of Turbulent Self-Noise Suppression and Sound Transmission of Acoustic Windows Made from Functionally Graded Material by Bing LI, Fu-Lin ZHOU, Jun FAN, Bin WANG, Liwen TAN

“…The STL, the turbulent self-noise reduction or a weighting function of the STL and turbulent self-noise reduction of FGM acoustic windows is chosen as the optimization objective. …”
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Frequency-constrained optimal power-gas flow with fast frequency response from power-to-gas units by Yu Liang, Xia Zhao

“…The substantial increase in renewable energy integration has resulted in a reduction in inertia and frequency regulation resources within the power system. …”
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Frailty in older adults patients: a prospective observational cohort study on subtype identification by Zhikai Yang, Chen Ji, Ting Wang, Wei He, Yuhao Wan, Min Zeng, Di Guo, Lingling Cui, Hua Wang

“…The logistic regression model exhibited robust predictive capability, with an AUC (Area under curve) of 0.88. …”
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An artificial intelligence model integrating culprit lesion diagnosis and risk assessment for acute coronary syndromeResearch in context by Peng Peng Xu, Bin Hu, Fan Zhou, Zhi Han Xu, Qian Chen, Tong Yuan Liu, Bang Jun Guo, Chang Sheng Zhou, Xin Wei Tao, Hong Yan Qiao, Jia Ni Zou, Xiang Ming Fang, Wen Cai Huang, Long Jiang Zhang

“…The diagnostic performance of five commonly used ML algorithms for identifying ACS culprit lesions was developed and compared within this cohort. …”
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A Critical Review of the Prospect of Integrating Artificial Intelligence in Infectious Disease Diagnosis and Prognosis by Shuaibu Abdullahi Hudu, Ahmed Subeh Alshrari, Esra’a Jebreel Ibrahim Abu-Shoura, Amira Osman, Abdulgafar Olayiwola Jimoh

“…This paper reviews how AI-driven models improve diagnostic accuracy, predict patient outcomes, and contribute to effective disease management. …”
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Modelling soil prokaryotic traits across environments with the trait sequence database ampliconTraits and the R package MicEnvMod by Jonathan Donhauser, Anna Doménech-Pascual, Xingguo Han, Karen Jordaan, Jean-Baptiste Ramond, Aline Frossard, Anna M. Romaní, Anders Priemé

“…We created the trait sequence database ampliconTraits, constructed by cross-mapping species from a phenotypic trait database to the SILVA sequence database and formatted to enable seamless classification of environmental sequences using the SINAPS algorithm. The R package MicEnvMod enables modelling of trait – environment relationships, combining the strengths of different model types and integrating an approach to evaluate the models' predictive performance in a single framework. …”
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