Revolutionizing Marine Stability: A Review of Cutting-Edge Gyro Stabilizer Designs and Techniques for Vessels by Wan Rahiman, Mohamad Hazwan Mohd Ghazali, Iskandar Al-Thani Mahmood

“…Despite these challenges, recent advancements in control algorithms and optimization techniques have improved gyro stabilizer adaptability under varying sea conditions. …”
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AI in biomedical science: innovations, challenges, and ethical perspectives by Aynur Aliyeva

“…In clinical practice, adaptive AI models have improved cochlear implant programming, leading to up to 30% gains in speech perception accuracy. …”
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A Combined Approach Using T2*-Weighted Dynamic Susceptibility Contrast MRI Perfusion Parameters and Radiomics to Differentiate Between Radionecrosis and Glioma Progression: A Proof... by José Pablo Martínez Barbero, Francisco Javier Pérez García, David López Cornejo, Marta García Cerezo, Paula María Jiménez Gutiérrez, Luis Balderas, Miguel Lastra, Antonio Arauzo-Azofra, José M. Benítez, Antonio Jesús Láinez Ramos-Bossini

“…This study aimed to develop and evaluate a machine learning model that integrates radiomics features and T2*-weighted Dynamic Susceptibility Contrast MRI perfusion (DSC MRI) parameters to improve diagnostic accuracy in distinguishing these entities. …”
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Automated classification of oral potentially malignant disorders and oral squamous cell carcinoma using a convolutional neural network framework: a cross-sectional studyResearch in... by Cristina Saldivia-Siracusa, Eduardo Santos Carlos de Souza, Arnaldo Vitor Barros da Silva, Anna Luíza Damaceno Araújo, Caíque Mariano Pedroso, Tarcília Aparecida da Silva, Maria Sissa Pereira Sant'Ana, Felipe Paiva Fonseca, Hélder Antônio Rebelo Pontes, Marcos G. Quiles, Marcio Ajudarte Lopes, Pablo Agustin Vargas, Syed Ali Khurram, Alexander T. Pearson, Mark W. Lingen, Luiz Paulo Kowalski, Keith D. Hunter, André Carlos Ponce de Leon Ferreira de Carvalho, Alan Roger Santos-Silva

“…Grad-CAM proved to be an outstanding tool to improve performance interpretation. Obtained results suggest that the adoption of DL models in healthcare could aid in diagnostic assistance and decision-making during clinical practice. …”
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Data-driven fault detection and positioning of eccentric rolls in roll-to-roll systems using wrap angle and sensor proximity by Yoonjae Lee, Minjae Kim, Jaehyun Noh, Gyoujin Cho, Changwoo Lee

“…Conclusively, the FCM is positioned as a pivotal tool for advancing industrial diagnostic processes, with future work suggested in the areas of adaptive feature extraction techniques and real-time model integration to improve the reliability and adaptability of R2R manufacturing.…”
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Classification of Individuals With COVID-19 and Post–COVID-19 Condition and Healthy Controls Using Heart Rate Variability: Machine Learning Study With a Near–Real-Time Monitoring C... by Carlos Alberto Sanches, Andre Felipe Henriques Librantz, Luciana Maria Malosá Sampaio, Peterson Adriano Belan

“…MethodsHRV indexes (SD of the normal-to-normal intervals [SDNN], root mean square of successive differences [RMSSD], low-frequency relative power [LF%], and high-frequency relative power [HF%]) were collected from 61 participants (n=21, 34% with active COVID-19; n=20, 33% with post–COVID-19 condition; and n=20, 33% healthy controls) using 2 standardized datasets. Classification models were developed using supervised machine learning algorithms (decision tree, support vector machines, k-nearest neighbor, and neural networks) and evaluated through cross-validation. …”
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Attentional bias for alcohol cues in visual search-Increased engagement, difficulty to disengage or both? by Janika Heitmann, Nienke C Jonker, Brian D Ostafin, Peter J de Jong

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The fusion of machine olfactory data and UV–Vis-NIR-MIR spectra enabled accurate prediction of key soil nutrients by Shuyan Liu, Lili Fu, Xiaomeng Xia, Jiamu Wang, Yvhang Cao, Xinming Jiang, Honglei Jia, Zengming Feng, Dongyan Huang

“…The findings demonstrated that introducing a self-attention procedure into the series splicing fusion strategy significantly improved the predictive performance. This highlights the synergistic benefits of integrating information from olfactory and spectral data sources. …”
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A Comparative Study of Breast Cancer Detection and Recurrence Prediction Using CatBoost Classifier by Rana Dhia’a Abdu-aljabar, Khansaa Dheya Aljafaar, Zinah Jaffar Mohammed Ameen, Hala A. Naman

“…This study delves into advanced machine learning techniques – CatBoost, XGBoost, Random Forest, SVM, KNN, and Naive Bayes – to improve the detection and prediction of breast cancer recurrence after healing. …”
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A semantic segmentation-based automatic pterygium assessment and grading system by Qingbo Ji, Qingbo Ji, Wanyang Liu, Wanyang Liu, Qingfeng Ma, Qingfeng Ma, Lijun Qu, Lin Zhang, Hui He

“…This study aims to develop an automated grading system combining deep learning and image processing techniques for precise pterygium evaluation.MethodsThe proposed system integrates two modules: 1) A semantic segmentation module utilizing an improved TransUnet architecture for pixel-level pterygium localization, trained on annotated slit-lamp microscope images from clinical datasets. 2) A severity assessment module employing enhanced curve fitting algorithms to quantify pterygium invasion depth in critical ocular regions. …”
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A strategy for network multi-layer information fusion based on multimodel in user emotional polarity analysis by Ronghua Wang, Peng Zhuang

“…The study employed multiple emotional analysis models to analyze emotions in text data. Then the emotional analysis results of different models were integrated to improve accuracy through a hierarchical information fusion strategy. …”
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Lightweight defocus deblurring network for curved-tunnel line scanning using wide-angle lenses by Shaojie Qin, Taiyue Qi, Xiaodong Huang, Xiao Liang

“…While existing deblurring algorithms can improve image quality, they often prioritize results over inference time, which is not ideal for high-speed tunnel image acquisition. …”
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Enhancing prediction of fluid-saturated fracture characteristics using deep learning super resolution by Manju Pharkavi Murugesu, Vignesh Krishnan, Anthony R. Kovscek

“…While past literature has offered solutions to improve resolution of CT rock images, including deep learning-based algorithms, our study uniquely focuses on improving dynamic, partially and fully fluid-saturated geological images. …”
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Mapping the landscape of Artificial intelligence for serious games in Health: An enhanced meta review by Xiya Tao, Nicolás Sáenz-Lechón, Martina Eckert

“…This paper presents an enhanced meta-review of artificial intelligence (AI) applications in serious games (SGs) for health, focusing on adaptation, personalisation, and real-time data processing to improve rehabilitation outcomes. A systematic review methodology, following PRISMA-ScR guidelines, was employed to analyse studies from 2017 to 2025, identifying the AI algorithms most frequently used to personalise gaming experiences, improve patient engagement, and increase treatment efficacy. …”
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Development experience of information system for ranking of academic and pedagogical staff by A. A. Chernousov, E. V. Vavilova

“…Experience in the implementation of the rating system in Plekhanov Russian University of Economics showed that the independent automated assessment of the activity efficiency of officers allows to improve the mechanism of planning and personnel management system, allows to create model of stimulation of the types of activity influencing increase of the place of University in the Russian and international ratings, and also creates conditions for positive dynamics of growth of level of qualification of academic and pedagogical staff. …”
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Assistance of Artificial Intelligence in Diagnosis of Vitreoretinal Lymphoma on Optical Coherence Tomography by Aidi Lin, Yuanyuan Peng, Tian Lin, Jun Dai, Jizhu Li, Tingkun Shi, Xixuan Ke, Xulong Liao, Danqi Fang, Man Chen, Huiyu Liang, Shirong Chen, Honghe Xia, Jingtao Wang, Zehua Jiang, Tao Li, Dan Liang, Shanshan Yu, Jing Luo, Ling Gao, Dawei Sun, Yih Chung Tham, Xinjian Chen, Haoyu Chen

“…The superiority of the model is shown with a higher F1 score (0.9310) compared with other state‐of‐the‐art algorithms (0.5487–0.9018) and three doctors whose clinical experiences range between 3 to 10 years without the help of the CS‐MTL (0.7773–0.8949). …”
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Intelligent collaborative management and control platform for continuous mining equipment in open-pit mines by Zhiyong LEI, Xiaolong MA, Shujun ZHAO, Shiming ZHANG, Bin YAN

“…This significantly enhances monitoring and control capabilities, achieving a high degree of synchronization between the digital model and physical operations. The platform delivers multiple functionalities, including comprehensive multi-machine synchronous monitoring, online fault self-diagnosis, and early warning systems, alongside improved multi-machine cooperative control efficiency. …”
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Optimized Two-Stage Anomaly Detection and Recovery in Smart Grid Data Using Enhanced DeBERTa-v3 Verification System by Xiao Liao, Wei Cui, Min Zhang, Aiwu Zhang, Pan Hu

“…The recovery mechanism achieves remarkably precise restoration with a mean absolute error (MAE) of only 0.0055 kWh, representing a 99.91% improvement compared to traditional ARIMA models and 98.46% compared to standard Anomaly Transformer models. …”
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Machine learning for defect condition rating of wall wooden columns in ancient buildings by Yufeng Li, Wu Ouyang, Zhenbo Xin, Houjiang Zhang, Shuqi Sun, Dian Zhang, Wenbo Zhang

“…The RBF neural network model achieved the highest accuracy (94.57 %) on the feature fusion dataset, while Grey Wolf Optimizer (GWO) optimization further improved accuracy to 96.74 %. …”
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Predicting Red Blood Cell Transfusion in Elective Cardiac Surgery: A Machine Learning Approach by Beatriz Lau, Daniel Ramos, Vera Afreixo, Luís M. Silva, Ana Helena Tavares, Miguel Martins Felgueiras, Diana Castro Paupério, João Firmino-Machado

“…These machine learning models demonstrate the potential to improve the accuracy of transfusion prediction at hospital admission, despite the absence of key variables such as surgeon identity and anaemia diagnosis.…”
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