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

“…The model demonstrated robust predictive power across multiple cohorts. Immune infiltration analysis revealed that the low-risk group exhibited higher levels of immune checkpoints (e.g., PD-1, PD-L1) and greater infiltration of B cells, CD4+ T cells, and CD8+ T cells, suggesting better responsiveness to immunotherapy. …”
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Joint Transmit-receive Beam Design of FDA-MIMO Dual-function Radar-communication Systems for Radio-frequency Stealth by Haozheng WU, Chenguang SHI, Jianjiang ZHOU

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A Distributed Machine Learning Model for Blue and Green Water Resources With Transferable Applications in Similar Climatic Zones by Zhibin Li, Haroon Sahotra, Sajjad Ahmad, Wei Wang, Zhe Yang, Pute Wu, Eakalak Khan, La Zhuo

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scAMZI: attention-based deep autoencoder with zero-inflated layer for clustering scRNA-seq data by Lin Yuan, Zhijie Xu, Boyuan Meng, Lan Ye

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Multi-Ethnic Analysis of Cardiac Pharmacogenetic Markers of Cytochrome P450 and Membrane Transporters Genes in the Russian Population by K. B. Mirzaev, D. S. Fedorinov, D. V. Ivashchenko, D. A. Sychev

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LIMITATIONS ON PRIMARY PERCUTANEOUS CORONARY INTERVENTION FOR ST-SEGMENT ELEVATION ACUTE MYOCARDIAL INFARCTION IN THE CLINICAL PRACTICE by V. V. Kashtalap, A. M. Kochergina, S. A. Makarov, V. Yu. Kheraskov, O. L. Barbarash

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Smoke and Fire-You Only Look Once: A Lightweight Deep Learning Model for Video Smoke and Flame Detection in Natural Scenes by Chenmeng Zhao, Like Zhao, Ka Zhang, Yinghua Ren, Hui Chen, Yehua Sheng

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Construction and Application of Feature Recommendation Model for Remote Sensing Interpretation of Rock Strata Based on Knowledge Graph by Liufeng Tao, Qirui Wu, Miao Tian, Zhong Xie, Jianguo Chen, Yueyu Wu, Qinjun Qiu

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Triple-layered security system: reliable and secured image communications over 5G and beyond networks by Tarek Srour, Mohsen A. M. El-Bendary, Mostafa Eltokhy, Atef E. Abouelazm

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Considering the effect of non-landslide sample selection on landslide susceptibility assessment by Youchen Zhu, Deliang Sun, Haijia Wen, Qiang Zhang, Qin Ji, Changming Li, Pinggen Zhou, Jianjun Zhao

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Rolling Bearing Remaining Useful Life Prognosis Method based on Improved CHSMM by Zhu Shuo, Bai Ruilin, Ji Feng

“…The experimental results show that the proposed method can accurately predict the remaining useful life of bearings.Compared with the original CHSMM algorithm,the accuracy of the degradation state recognition is increased by12%,and the accuracy of remaining useful life prediction is increased by 23%.…”
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AI-Assisted Design of Drain-Extended FinFET With Stepped Field Plate for Multi-Purpose Applications by Xiaoyun Huang, Hongyu Tang, Chenggang Xu, Yuxuan Zhu, Yan Pan, Dawei Gao, Yitao Ma, Kai Xu

“…Moreover, within an AI-assisted design framework, predictive modeling and multi-objective optimization of the device are accomplished using Kolmogorov–Arnold Networks (KAN) and the Nondominated Sorting Genetic Algorithm (NSGA-III). …”
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Leveraging multiple cell-death patterns based on machine learning to decipher the prognosis, immune, and immune therapeutic response of soft tissue sarcoma by Binfeng Liu, Shasha He, Chenbei Li, Zijian Xiong, Zhaoqi Li, Chengyao Feng, Hua Wang, Chao Tu, Zhihong Li

“…The independence test and comparison with previously published models further confirmed the stability and quality of these signatures for survival prediction in STS. The nomogram, comprising the cell death score (CDS) and clinical features, exhibited excellent predictive performance. …”
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Construction and validation of immune prognosis model for lung adenocarcinoma based on machine learning by Jinyu Zheng, Xiaoyi Xu, Xianguo Chen, Xianshuai Li, Miao Fu, Yiping Zheng, Jie Yang

“…A multivariate Cox regression model was built to predict survival. Model performance was assessed by time-dependent ROC and ANN models. …”
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The role of advanced machine learning in COVID-19 medical imaging: A technical review by Abdul Muiz Fayyaz, Said Jadid Abdulkadir, Shahab Ul Hassan, Safwan Mahmood Al-Selwi, Ebrahim Hamid Sumiea, Lareib Fatima Talib

“…It focuses on approaches such as Deep Learning (DL) algorithms and Transfer Learning, which have demonstrated significant potential in developing automated, accurate COVID-19 detection systems. …”
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Efficient Frequency-Domain Block Equalization for Mode-Division Multiplexing Systems by Yifan Shen, Jianyong Zhang, Shuchao Mi, Guofang Fan, Muguang Wang

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Machine learning model for diagnosing salivary gland adenoid cystic carcinoma based on clinical and ultrasound features by Huan-Zhong Su, Zhi-Yong Li, Long-Cheng Hong, Yu-Hui Wu, Feng Zhang, Zuo-Bing Zhang, Xiao-Dong Zhang

“…The least absolute shrinkage and selection operator (LASSO) regression identified optimal features, which were subsequently utilized to construct predictive models employing five ML algorithms. The performance of the models was evaluated across a comprehensive array of learning metrics, prominently the area under the receiver operating characteristic curve (AUC). …”
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A Hybridization of Machine Learning and NSGA-II for Multi-Objective Optimization of Surface Roughness and Cutting Force in ANSI 4340 Alloy Steel Turning by Anh-Tu Nguyen, Van-Hai Nguyen, Tien-Thinh Le, Nhu-Tung Nguyen

“…A hybridization of Machine Learning (ML) algorithms and a Non-Dominated Sorting Genetic Algorithm (NSGA-II) is applied to find the Pareto solution. …”
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Using fishery-related data, scientific expertise, and machine learning to improve marine habitat mapping in northeastern Mediterranean waters by Loukas Katikas, Sofia Reizopoulou, Paraskevi Drakopoulou, Vassiliki Vassilopoulou

“…Two machine-learning algorithms, i.e., random forest classifier (RFC) and gradient boosting classifier, were trained on the entire national-scale dataset and subsequently applied to assess their performance in predicting habitat types in the Saronikos Gulf (regional scale) using various environmental factors as predictors. …”
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VIS/NIR Spectroscopy as a Non-Destructive Method for Evaluation of Quality Parameters of Three Bell Pepper Varieties Based on Soft Computing Methods by Meysam Latifi Amoghin, Yousef Abbaspour-Gilandeh, Mohammad Tahmasebi, Mohammad Kaveh, Hany S. El-Mesery, Mariusz Szymanek, Maciej Sprawka

“…To optimize wavelength selection, support vector machines (SVMs) were combined with genetic algorithms (GAs), particle swarm optimization (PSO), ant colony optimization (ACO), and imperial competitive algorithm (ICA). …”
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