Prediction of pharmacokinetic/pharmacodynamic properties of aldosterone synthase inhibitors at drug discovery stage using an artificial intelligence-physiologically based pharmacok... by Mengjun Zhang, Keheng Wu, Sihui Long, Xiong Jin, Bo Liu

“…On a web-based platform, an AI-PBPK model, integrating machine learning and a classical PBPK model for the PK simulation of ASIs, was developed. …”
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Development of Machine Learning Prediction Models to Predict ICU Admission and the Length of Stay in ICU for COVID‑19 Patients Using a Clinical Dataset Including Chest Computed Tom... by Seyed Salman Zakariaee, Negar Naderi, Hadi Kazemi-Arpanahi

“…For predicting the ICU admission of COVID-19 patients, k-nearest neighbors (k-NN) yielded better performance than J48, support vector machine, multi-layer perceptron, Naïve Bayes, logistic regression, random forest (RF), and XGBoostbased ML models. …”
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Novel machine learning approach for enhanced smart grid power use and price prediction using advanced shark Smell-Tuned flexible support vector machine by Yuwei Duan, Zihan Xu, Huiyi Chen, Yue Wang

“…PCA reduces dimensionality by extracting pre-processed data characteristics. Optimized and tested FSVM models can anticipate smart grid power use and pricing. …”
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A hybrid fuzzy logic–Random Forest model to predict psychiatric treatment order outcomes: an interpretable tool for legal decision support by Alexandre Hudon, Alexandre Hudon, Alexandre Hudon, Alexandre Hudon

“…Future work should aim to validate the model across other jurisdictions, incorporate more advanced natural language processing for semantic feature extraction, and explore dynamic rule optimization techniques. …”
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Rapid Path Planning Algorithm for Percutaneous Rigid Needle Biopsy Based on Optical Illumination Principles by Jian Liu, Shuai Kang, Juan Ren, Dongxia Zhang, Bing Niu, Kai Xu

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Towards Cleaner Cities: Estimating Vehicle-Induced PM_2.5 with Hybrid EBM-CMA-ES Modeling by Saleh Alotaibi, Hamad Almujibah, Khalaf Alla Adam Mohamed, Adil A. M. Elhassan, Badr T. Alsulami, Abdullah Alsaluli, Afaq Khattak

“…This study proposes a Hybrid Explainable Boosting Machine (EBM) framework, optimized using the Covariance Matrix Adaptation Evolution Strategy (CMA-ES), to predict vehicle-related PM_2.5 concentrations and analyze contributing factors. …”
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Outlook towards deployable continual learning for particle accelerators by Kishansingh Rajput, Sen Lin, Auralee Edelen, Willem Blokland, Malachi Schram

“…Particle accelerators are high power complex machines. To ensure uninterrupted operation of these machines, thousands of pieces of equipment need to be synchronized, which requires addressing many challenges including design, optimization and control, anomaly detection and machine protection. …”
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Self-adaptive evolutionary neural networks for high-precision short-term electric load forecasting by Muhammad Abbas, Yanbo Che, Sarmad Maqsood, Muhammad Zain Yousaf, Mustafa Abdullah, Wajid Khan, Saqib Khalid, Mohit Bajaj, Mohammad Shabaz

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Civil aircraft longitudinal center-of-gravity position estimation combining domain knowledge and simulation data by Shaobo Zhai, Guangwen Li, Xinyang Du, Mingshan Hou

“…Building on this foundation, extensive simulation data are generated using a nonlinear six-degree-of-freedom aircraft model with variable mass. A novel aircraft LCG position estimation algorithm combining extreme learning machine (ELM) and particle swarm optimization (PSO) is developed. …”
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A Gene Ontology-Based Pipeline for Selecting Significant Gene Subsets in Biomedical Applications by Sergii Babichev, Oleg Yarema, Igor Liakh, Nataliia Shumylo

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A comparative study of deep reinforcement learning for crop production management by Joseph Balderas, Dong Chen, Yanbo Huang, Li Wang, Ren-Cang Li

“…RL models aim to optimize long-term rewards by continuously interacting with the environment, making them well-suited for tackling the uncertainties and variability inherent in crop management. …”
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Bayesian optimization with Optuna for enhanced soil nutrient prediction: a comparative study with genetic algorithm and particle swarm optimization by Bamidele A. Dada, Nnamdi I. Nwulu, Seun O. Olukanmi

“…The investigation confirms that Optuna-optimized models are at least 13 % more precise than GA and PSO models. …”
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Three-Dimensional In Situ Stress Distribution in a Fault Fracture Reservoir, Linnan Sag, Bohai Bay Basin by Jiageng Liu, Yanzhong Wang, Jing Li, Xiaoyu Meng, Jiayi Teng, Zhicheng Wang, Mingzhi Li, Rui Zhu

“…Reverse modeling and optimization reconstruction are used to construct a three-dimensional geomechanical model of the fracture system. …”
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Addressing challenges in deposition efficiency and material compatibility in low-pressure cold spray systems by Rizaldy Hakim Ash Shiddieqy, Alief Wikarta, Agus Sigit Pramono, Suwarno, Yohanes, Jung-Ting Tsai

“…Furthermore, the paper discusses emerging innovations such as advanced nozzle designs, adaptive compressor systems, sustainable carrier gas alternatives, and real-time process monitoring. Significantly, machine learning-based predictive models are identified as a transformative approach to optimize LPCS operations, enabling real-time control and reducing dependence on traditional trial-and-error experimentation. …”
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Multi-objective federated learning traffic prediction in vehicular network for intelligent transportation system by Arulmurgan Aalavanthar, Famila S., Shanmugam Sundaramurthy, Stefano Cirillo, Giandomenico Solimando, Giuseppe Polese

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Construction and Evaluation of a Cross-Regional and Cross-Year Monitoring Model for Millet Canopy Phenotype Based on UAV Multispectral Remote Sensing by Peng Zhao, Yuqiao Yan, Shujie Jia, Jie Zhao, Wuping Zhang

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Towards Automated Cadastral Map Improvement: A Clustering Approach for Error Pattern Recognition by Konstantinos Vantas, Vasiliki Mirkopoulou

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Mathematical models and artificial intelligence for studying the ventricular dyssynchrony and improving the effectiveness of cardiac resynchronization therapy by T. M. Nesterova, V. Yu. Kabak, D. S. Lebedev, O. E. Solovyova

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Predictive Analysis of Mechanical Properties in Cu-Ti Alloys: A Comprehensive Machine Learning Approach by Mihail Kolev

“…The dataset was divided into training, validation, and test sets, with a Random Forest Regressor model being trained and optimized using GridSearchCV. …”
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Classification of Vaginal Cleanliness Grades through Surface‐Enhanced Raman Spectral Analysis via The Deep‐Learning Variational Autoencoder–Long Short‐Term Memory Model by Jia‐Wei Tang, Xin‐Ru Wen, Hui‐Min Chen, Jie Chen, Kun‐Hui Hong, Quan Yuan, Muhammad Usman, Liang Wang

“…Finally, the reliability of the optimal model is tested using blind test data (N = 10/group for each cleanliness level). …”
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