Automatic identification of Dong Son antique glass artifacts using evolving learning by Anh-Khoi Ngo-Ho, Hoang-Bac Bui, Van-Trieu Pham

“…This approach, which has gained prominence in the field of archaeology worldwide over the past five years, aims to integrate advanced technology into Vietnamese archaeology. Our research is motivated by the unique conditions present in archaeology, where we seek to employ evolving learning algorithms to archaeological databases, comparing and selecting the most suitable model that aligns with the archeological dataset's performance. …”
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Self-organizing maps to evaluate optimal strategies for balancing binary class distributions: a methodological approach by Alberto Nogales, Diego Guadalupe, Álvaro J. García-Tejedor

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Machine learning models for predicting metabolic dysfunction-associated steatotic liver disease prevalence using basic demographic and clinical characteristics by Gangfeng Zhu, Yipeng Song, Zenghong Lu, Qiang Yi, Rui Xu, Yi Xie, Shi Geng, Na Yang, Liangjian Zheng, Xiaofei Feng, Rui Zhu, Xiangcai Wang, Li Huang, Yi Xiang

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Machine learning-based diagnostic model of lymphatics-associated genes for new therapeutic target analysis in intervertebral disc degeneration by Maoqiang Lin, Maoqiang Lin, Shaolong Li, Yabin Wang, Yabin Wang, Guan Zheng, Guan Zheng, Fukang Hu, Fukang Hu, Qiang Zhang, Qiang Zhang, Pengjie Song, Haiyu Zhou, Haiyu Zhou

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A Weighted Two-Level Bregman Method with Dictionary Updating for Nonconvex MR Image Reconstruction by Qiegen Liu, Xi Peng, Jianbo Liu, Dingcheng Yang, Dong Liang

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Advancements in biomarkers and machine learning for predicting of bronchopulmonary dysplasia and neonatal respiratory distress syndrome in preterm infants by Hanieh Talebi, Seyed Alireza Dastgheib, Maryam Vafapour, Reza Bahrami, Mohammad Golshan-Tafti, Mahsa Danaei, Sepideh Azizi, Amirhossein Shahbazi, Melina Pourkazemi, Maryam Yeganegi, Amirmasoud Shiri, Ali Masoudi, Heewa Rashnavadi, Hossein Neamatzadeh

“…Key predictors of BPD severity include elevated cytokines like Interleukin-6 (IL-6) and Tumor Necrosis Factor-alpha (TNF-α), as well as inflammatory markers such as the Neutrophil-to-Lymphocyte Ratio (NLR) and soluble gp130. Research into endoplasmic reticulum stress-related genes, differentially expressed genes, and ferroptosis-related genes provides valuable insights into BPD's pathophysiology. …”
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SUMOylation-related genes define prognostic subtypes in stomach adenocarcinoma: integrating single-cell analysis and machine learning analyses by Kaiping Luo, Kaiping Luo, Donghui Xing, Donghui Xing, Xiang He, Yixin Zhai, Yanan Jiang, Hongjie Zhan, Zhigang Zhao

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Generation of Spatial Structure of Urban Parks Based on Spatial Analysis of Agent-Based Models by Huizi KONG, Tianming LIU, Jiajie LIAO, Liu CUI

“…ObjectiveThis research aims to leverage the advances of computer algorithms to provide scientific analytical methods for spatial simulation and offer a more objective approach to reflect the natural operational laws of interdependencies between elements in the real physical world for landscape design. …”
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Unveiling the effect of urinary xenoestrogens on chronic kidney disease in adults: A machine learning model by Bowen Zhang, Liang Chen, Tao Li

“…The synergistic effects suggested that managing urinary MeP levels could be essential for the effective control of CKD. In summary, our research highlights the significant predictive potential of XEs for CKD, especially MeP, MCNP, and TCS.…”
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Assessing Huanglongbing Severity and Canopy Parameters of the Huanglongbing-Affected Citrus in Texas Using Unmanned Aerial System-Based Remote Sensing and Machine Learning by Ittipon Khuimphukhieo, Jose Carlos Chavez, Chuanyu Yang, Lakshmi Akhijith Pasupuleti, Ismail Olaniyi, Veronica Ancona, Kranthi K. Mandadi, Jinha Jung, Juan Enciso

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Correlation Between Clinical Indicators and Liver Pathology in Children with Chronic Hepatitis B by Chenyang Huang, Ying Lu, Ziwei Wang, Qiyu Jiang, Yi Dong, Lili Cao, Jianguo Yan, Zhiqiang Xu, Fuchuan Wang, Yinjie Gao, Junliang Fu, Min Zhang, Fu-Sheng Wang

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Harnessing artificial intelligence for predictive modelling in oral oncology: Opportunities, challenges, and clinical Perspectives by Vishnu Priya Veeraraghavan, Shikhar Daniel, Arun Kumar Dasari, Kaladhar Reddy Aileni, Chaitra patil, Santosh R. Patil

“…Additionally, challenges such as interpretability, data accessibility, regulatory compliance, and legal implications are addressed along with future research directions and the potential impact of AI on oral oncology care.…”
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Energy and Spectrum Efficient Wireless Sensor Networks by Gianni Pasolini, George Alexandropoulos, Lorenzo Mucchi, Javier Prieto, Yuan Shen

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Personalized treatment decision-making using a machine learning-derived lactylation signature for breast cancer prognosis by Simin Min, Xiaonan Zhang, Yuling Liu, Weiqiang Wang, Jingwen Guan, Yuyan Chen, Meng Sun, Ziheng Wang, Tao Wang

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Bidirectional Wireless Charging System for Electric Vehicles: A Review of Power Converters and Control Techniques in V2G Application by Subia Meraj, Saad Mekhilef, Marizan Binti Mubin, Harikrishnan Ramiah, Mehdi Seyedmahmoudian, Alex Stojcevski

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BanglaTaka: A dataset for classification of Bangladeshi banknotesMendeley Data by Md. Naimul Islam Nuhash, Sadia Akter

“…The dataset is suitable for training and testing machine learning algorithms for currency classification and it supports research in financial automation and deep learning-based classification algorithms. …”
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Driver anomaly detection in cargo terminal by Shahab Emaani, Abbas Saghaei

“…Subsequently, Isolation Forest, KNN, and HBOS algorithms are applied to detect abnormal behavior using data mining techniques. …”
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Performance evaluation, optimization and dynamic decision in blockchain systems: a recent overview by Quan-Lin Li, Yan-Xia Chang, Qing Wang

“…Important examples include (a) performance evaluation: Markov processes, queuing theory, Markov reward processes, random walks, fluid and diffusion approximations, and martingale theory; (b) performance optimization:Linear programming, nonlinear programming, integer programming, and multi-objective programming; (c) optimal control and dynamic decision: Markov decision processes, and stochastic optimal control; and (d) artificial intelligence: Machine learning, deep reinforcement learning, and federated learning. So far, a little research has focused on these research lines. We believe that the basic theory with mathematical methods, algorithms and simulations of blockchain systems discussed in this paper will stronglysupport future development and continuous innovation of blockchain technology.…”
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Artificial Neural Network Text Generation as a New Type of Masking the Authorship by Ogorelkov Igor', Mahaeva Elizaveta

“…The prospects for further research lie in an in-depth study of complex AI-generated text structures, e.g., preloaded idiosyncratic texts. …”
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Unsupervised Learning for Heart Disease Prediction: Clustering-Based Approach by Jetty Janani., Sk Sajida Sultana., Polepalle Ranga Bhavitha., Parusu Vishwitha.

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