A Rapid Identification Method for Cottonseed Varieties Based on Near-Infrared Spectral and Generative Adversarial Networks by Qingxu Li, Hao Li, Renhao Liu, Xiaofeng Dong, Hongzhou Zhang, Wanhuai Zhou

“…Data augmentation using GAN-CNIRD-generated cottonseed data improved the accuracy of the three optimal models by 6%, 5%, and 6%, respectively. …”
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Machine learning-based brain magnetic resonance imaging radiomics for identifying rapid eye movement sleep behavior disorder in Parkinson’s disease patients by Yandong lian, Yibin Xu, Linlin Hu, Yuguo Wei, Zhaoge Wang

“…Furthermore, based on the optimal cut-off value of the model, subjects were categorized into low- and high-risk groups, and differences in the actual number of RBD patients between the two sets were compared to assess the clinical effectiveness of the model. …”
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A Multi-Branch Convolution and Dynamic Weighting Method for Bearing Fault Diagnosis Based on Acoustic–Vibration Information Fusion by Xianming Sun, Yuhang Yang, Changzheng Chen, Miao Tian, Shengnan Du, Zhengqi Wang

“…This model aims to enhance feature fusion, dynamically adapt to signal characteristics, optimize feature selection, and reduce computational complexity. …”
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Analysis of types of medical interventions for patients with pancreatic adenocarcinoma in hospitals of Saint Petersburg for the period from 2014 to 2020 by V. E. Moiseenko, A. V. Pavlovsky, D. A. Granov, L. V. Kochorova, N. I. Vishnjakov, V. V. Hizha, A. V. Yazenok, N. Ju. Shirshova, L. A. Solovyova

“…The data obtained from such an analysis can become the basis for the development of algorithms and programs for optimizing the provision of care for patients suffering from this pathology. …”
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Explainable Boosting Machines Identify Key Metabolomic Biomarkers in Rheumatoid Arthritis by Fatma Hilal Yagin, Cemil Colak, Abdulmohsen Algarni, Ali Algarni, Fahaid Al-Hashem, Luca Paolo Ardigò

“…EBM, LightGBM, and AdaBoost algorithms were applied to generate a discriminatory model between RA and controls. …”
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Operational factors influencing quality control in ore milling: a systematic review by Eliana de Jesus Lopes, Guilherme Graciano dos Santos, Adriano Ricardo Almeida Alexandre

“…The identified studies explore advanced techniques such as algorithms and mathematical modeling to optimize the grinding process and improve product quality. …”
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Innovative approach for gauge-based QPE in arid climates: comparing neural networks and traditional methods by Bayan Banimfreg, Ernesto Damiani, Vesta Afzali Gorooh, Duncan Axisa, Luca Delle Monache, Youssef Wehbe

“…These improvements highlight the model’s ability to assimilate diverse climatic and topographical inputs for more accurate rainfall prediction, particularly in areas where conventional methods fall short due to sparse or irregular precipitation. …”
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Lightweight Indoor Positioning System Based on Multiple Self-Learning Features and Key Frame Classification by C. Wang, K. Bi, B. Zhao, M. Li, Y. Chen, S. Tao, J. Yang

“…It has significant optimizations compared with conventional visual solutions in terms of preprocessing data collection, algorithm performance consumption, and versatility.…”
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Application and prospects of machine learning for rockfalls, landslides and debris flows by Jiazhu WANG, Yongbo TIE, Yongjian BAI, Yanchao GAO, Donghui WANG, Mingzhi ZHANG

“…Future research should prioritize enhancing data quality and quantity, optimizing model interpretability, improving model reliability and generalization, and establishing real-time monitoring and warning systems for automatic identification and rapid response to geological hazards. …”
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Radiomics analysis of thoracic vertebral bone marrow microenvironment changes before bone metastasis of breast cancer based on chest CT by Hao-Nan Zhu, Yi-Fan Guo, YingMin Lin, Zhi-Chao Sun, Xi Zhu, YuanZhe Li

“…Multiple machine learning algorithms were utilized to construct various radiomics models for predicting the risk of bone metastasis, and the model with optimal performance was integrated with clinical features to develop a nomogram. …”
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ICT-Net: A Framework for Multi-Domain Cross-View Geo-Localization with Multi-Source Remote Sensing Fusion by Min Wu, Sirui Xu, Ziwei Wang, Jin Dong, Gong Cheng, Xinlong Yu, Yang Liu

“…To facilitate practical deployment, we propose a deep embedding clustering algorithm optimized for rapid parsing of geo-localization information. …”
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Sustainable Energy and Exergy Analysis in Offshore Wind Farms Using Machine Learning: A Systematic Review by Hamid Reza Soltani Motlagh, Seyed Behbood Issa-Zadeh, Abdul Hameed Kalifullah, Arife Tugsan Isiacik Colak, Md Redzuan Zoolfakar

“…By integrating theoretical insights with empirical evidence, this study proposes a unified framework that leverages ML algorithms to optimize turbine performance, reduce maintenance costs, and minimize environmental impacts. …”
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Research on Methods for the Recognition of Ship Lights and the Autonomous Determination of the Types of Approaching Vessels by Xiangyu Gao, Yuelin Zhao

“…Firstly, to address the challenges of the small target characteristics of ship lights and complex environmental interference, an improved YOLOv8 model is developed: The dilation-wise residual (DWR) module is introduced to optimize the feature extraction capability of the C2f structure. …”
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Analysis of soil salinization and land use change under water conservation retrofit in the Hetao irrigation district by Yi Zhao, Shuya Yang, Haibin Shi, Haoqi Han, Yunlei Dong, Xianyue Li, Jianwen Yan, Yan Yan, Xu Dou, Feng Tian, Qingfeng Miao

“…After the water conservation retrofit, non-saline soil increased by 326.5 km2, indicating improved soil conditions. The overall accuracy of the Gradient Boosting Tree classification model is 95.00 % and the Kappa coefficient is 0.93, which is the optimal model for land use type classification. …”
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The Emerging Role of Artificial Intelligence in Dermatology: A Systematic Review of Its Clinical Applications by Ernesto Martínez-Vargas, Jeaustin Mora-Jiménez, Sebastian Arguedas-Chacón, Josephine Hernández-López, Esteban Zavaleta-Monestel

“…Conclusions: AI has demonstrated robust clinical potential in dermatology, particularly in cancer detection and workflow optimization. However, further studies are required to address challenges such as algorithmic bias, data privacy, and regulatory oversight. …”
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River Surface Space–Time Image Velocimetry Based on Dual-Channel Residual Network by Ling Gao, Zhen Zhang, Lin Chen, Huabao Li

“…An adaptive threshold Sobel operator in the edge channel improves the model’s ability to extract edge features in STI. …”
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IDENTIFYING IMPORTANT GENES IN OVARIAN CANCER FROM HIGH-DIMENSIONAL MICROARRAY DATA USING SIFS-CART METHOD by Ni Kadek Emik Sapitri, Umu Sa'adah, Nur Shofianah

“…Many studies only focus on improving the machine learning classification algorithms to achieve higher performance. …”
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Programmed cell death signatures-driven microglial transformation in Alzheimer’s disease: single-cell transcriptomics and functional validation by Mi-Mi Li, Ying-Xia Yang, Ya-Li Huang, Shu-Juan Wu, Wan-Li Huang, Li-Chao Ye, Ying-Ying Xu

“…An integrated machine learning framework, combining 12 algorithms was used to construct a PCDS model. The performance of PCDS was validated using multiple independent cohorts. …”
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Duck Egg Crack Detection Using an Adaptive CNN Ensemble with Multi-Light Channels and Image Processing by Vasutorn Chaowalittawin, Woranidtha Krungseanmuang, Posathip Sathaporn, Boonchana Purahong

“…In current practice, human inspectors use standard white light for crack detection, and many researchers have focused primarily on improving detection algorithms without addressing lighting limitations. …”
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Can Stereoscopic Density Replace Planar Density for Forest Aboveground Biomass Estimation? A Case Study Using Airborne LiDAR and Landsat Data in Daxing’anling, China by Xuan Mu, Dan Zhao, Zhaoju Zheng, Cong Xu, Jinchen Wu, Ping Zhao, Xiaomin Li, Yong Pang, Yujin Zhao, Tianyu An, Yuan Zeng, Bingfang Wu

“…The results of 10-fold cross-validation demonstrated the superiority of the stereo method over the planar method, with RF outperforming SLR. The optimal RF-based stereo model of H_AM (R² = 0.65, rRMSE = 26.05%) significantly improved AGB estimation compared to the planar model (R² = 0.59, rRMSE = 30.41%). …”
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