SOME ASPECTS OF SCANNING LASER OPHTHALMOSCOPY IN THE DIAGNOSTICS OF OPHTHALMOPATHOLOGY by S. A. Kochergin, S. Yu. Slonimsky, A. A. Ovsyanko, O. D. Gupalo

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Posture Recognition and Behavior Tracking in Swimming Motion Images under Computer Machine Vision by Zheng Zhang, Cong Huang, Fei Zhong, Bote Qi, Binghong Gao

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Self-organized cyber physical power system blockchain architecture and protocol by Ting Yang, Feng Zhai, Jialin Liu, Meng Wang, Haibo Pen

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Susceptibility assessment of freeze-thaw erosion induced debris flow using random forest, Eastern Tibetan Plateau by Yongjie Yang, Yongjie Yang, Yongjie Yang, Yuqi Zhang, Yuqi Zhang, Yuqi Zhang, Hai Huang, Hai Huang, Jinsong Zhu, Jinsong Zhu, Jinsong Zhu, Qiwei Lv, Qiwei Lv, Qiwei Lv, Jiang Peng, Jiang Peng

“…Subsequently, the freeze-thaw erosion index, a new control factor gauging the intensity of freeze-thaw erosion in the study area, was incorporated, and the susceptibility assessment was also conducted using the Random Forest Algorithm (Freeze-thaw erosion model, FEM). The results show that FEM improved accuracy by 0.457 and AUC by 0.0541 compared to NFEM, indicating enhanced predictive performance. …”
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Comparison of Recognition Techniques to Classify Wear Particle Texture by Mohammad Laghari, Ahmed Hassan, Mahmoud Haggag, Addy Wahyudie, Motaz Tayfor, Abdallah Elsayed

“…This analysis plays a vital role in predictive maintenance by revealing component degradation in machinery. …”
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Monte Carlo Simulation and Experimental Validation for Radiation Protection with Multiple Complex Source Terms and Deep Penetration for a Radioactive Liquid Waste Cementation Facil... by Wenqian Li, Xuegang Liu, Sheng Fang, Xueliang Fu, Kaiqiang Guo

“…The complex shielding also leads to a deep penetration problem; hence, the optimization algorithm and variance reduction techniques were adopted. …”
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Comparison of pulse pressure and stroke volume variations measured by three monitors in high-risk surgical patients by Barbora Cenková, Miloš Chobola, Vladimír Šrámek, Michal Šitina, Pavel Suk

“…We aimed to compare the baseline values, fluctuation and predictive value for FR of PPV and SVV measured by three minimally invasive monitors. …”
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Federated Reinforcement Learning-Based Dynamic Resource Allocation and Task Scheduling in Edge for IoT Applications by Saroj Mali, Feng Zeng, Deepak Adhikari, Inam Ullah, Mahmoud Ahmad Al-Khasawneh, Osama Alfarraj, Fahad Alblehai

“…This algorithm is compared to DQN, DDQN, Dueling DQN, and Dueling DDQN models using Non-IID EMNIST, IID EMNIST datasets, and with the Crop Prediction dataset. …”
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Computational methods and artificial intelligence-based modeling of magnesium alloys: a systematic review of machine learning, deep learning, and data-driven design and optimizatio... by Hanxuan Wang, Raman Kumar, Raman Kumar, Ashutosh Pattanaik, Rajender Kumar, Rajender Kumar, Ali Saeed Owayez Khawaf Aljaberi, Mayada Ahmed Abass

“…The review highlights the extensive application of models, including Artificial Neural Networks, Convolutional Neural Networks, and hybrid frameworks that combine ML with optimization algorithms or physical simulations. These approaches enhance predictions on mechanical properties, microstructural changes, corrosion behavior, and processing results of Mg alloys. …”
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Adaptive Differential Privacy Cox-MLP Model Based on Federated Learning by Jie Niu, Runqi He, Qiyao Zhou, Wenjing Li, Ruxian Jiang, Huimin Li, Dan Chen

“…Experimental results on simulated and clinical datasets demonstrate improved predictive performance and robust privacy protection.…”
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Communicating the use of artificial intelligence in agricultural and environmental research by Aaron Lee M. Daigh, Samira H. Daroub, Peter M. Kyveryga, Mark E. Sorrells, Nithya Rajan, James A. Ippolito, Endy Kailer, Christine S. Booth, Umesh Acharya, Deepak Ghimire, Saurav Das, Bijesh Maharjan, Yufeng Ge

“…Clear communication is perhaps more necessary with AI than previous technologies due to its broad and flexible spectrum of uses, the “black‐box” nature of deep‐learning algorithms, and ongoing debates regarding AI's predictive power versus knowledge of first‐principles mechanistic and process‐based theories and models. …”
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Using rule-based machine learning for candidate disease gene prioritization and sample classification of cancer gene expression data. by Enrico Glaab, Jaume Bacardit, Jonathan M Garibaldi, Natalio Krasnogor

“…Increasing the interpretability of prediction models while retaining a high accuracy would help to exploit the information content in microarray data more effectively. …”
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MobileNetV3: an efficient deep learning-based feature selection and classification technique for cardiovascular disease by B. Dhanalaxmi, B. Naveen Kumar, Yeligeti Raju, Rama Seshagiri Rao Channapragada

“…Unfortunately, most currently utilized cardiovascular disease prediction algorithms could not achieve higher accuracy due to inadequate forecasting methodology and data-recognized techniques. …”
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Emerging Trends in the Integrating Remote Sensing and Machine Learning for Groundwater Resources Management: A Bibliometric Study by Abolfazl Akbarpour, Moein Tosan, Raziyeh Shamshirgaran

“…Sustainable management of groundwater resources, as a multifaceted challenge in water sciences, necessitates the adoption of novel computational approaches for monitoring, modeling, and predicting dynamics. This research investigates the status and outlines future research directions in advanced remote sensing applications for groundwater management from 2000 to 2024. …”
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Identification of Key Nucleotide Metabolism Genes in Diabetic Retinopathy Based on Bioinformatics Analysis and Experimental Verification by Wei Wang, Jianyang Gong

“…The miRNA and transcription factor (TF) predictions, biomarker-targeting drugs, and molecular docking were implemented separately. …”
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CTSS in the tumor microenvironment links immune escape and immunotherapy sensitivity in kidney renal clear cell carcinoma by Hanjing Zhou, Jun Ying, Xuchun Xu, Jian Huang

“…Employing advanced machine learning (ML) algorithms, we identified Cathepsin S (CTSS) as the most pivotal tumor suppressor, with elevated CTSS expression consistently predicting improved survival across multiple independent cohorts. …”
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Identifying Behaviours Indicative of Illegal Fishing Activities in Automatic Identification System Data by Yifan Zhou, Richard Davies, James Wright, Stephen Ablett, Simon Maskell

“…To mitigate these issues, our prediction algorithm only uses the sequence of ports the ships visited, as inferred from the positions reported in AIS messages. …”
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Identification of lipid metabolism related immune markers in atherosclerosis through machine learning and experimental analysis by Hang Chen, Biao Wu, Biao Wu, Kunyu Guan, Liang Chen, Kangjie Chai, Maoji Ying, Dazhi Li, Weicheng Zhao

“…This research provides a valuable approach for the predictive diagnosis and targeted therapy of atherosclerosis.…”
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A Data-Driven Approach for Energy Consumption Modeling and Optimization of Welding Robot Systems by Minling Pan, Bingqi Jia, Lei Zhang, Haihong Pan, Lin Chen

“…To solve the optimization problem, an improved whale optimization algorithm (IWOA) was employed. Experimental validations with a welding robot demonstrate that the proposed method not only accurately predicted EC with a MAPE of 2.66% but also reduced the robot system’s EC by 6.72%, outperforming the traditional method focused solely on joint motor EC, which achieved a 4.08% reduction. …”
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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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