Multi-omics analysis and experiments uncover the link between cancer intrinsic drivers, stemness, and immunotherapy in ovarian cancer with validation in a pan-cancer census by Yilin Li, Cen Chen, Xiaoyu Ji, Ningxiao Jiang, Fei Wang, Xiangqian Gao, Weiwei Chen, Qiang Tang, Yan Li, Shinan Zhang, Gaofeng Qin, Yingjiang Xu, Yanlin Wang, Lingwen Kong, Lei Han, Jie Mei

“…We then developed the CSCI to predict the prognosis and response to immunotherapy in ovarian cancer patients using advanced machine learning algorithms. …”
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Soft computing approaches of direct torque control for DFIM Motor's by Zakariae Sakhri, El-Houssine Bekkour, Badre Bossoufi, Nicu Bizon, Mishari Metab Almalki, Thamer A.H. Alghamdi, Mohammed Alenezi

“…This article provides a critical analysis of the following cutting-edge methods: DTC with Space Vector Modulation (DTC-SVM), DTC based on Fuzzy Logic (DTC-FL), DTC using Artificial Neural Networks (DTC-ANN), DTC optimized by Genetic Algorithms (DTC-GA), DTC with Ant Colony Optimization (DTC-ACO), DTC with rooted tree optimization (DTC-RTO), Sliding Mode Control (DTC-SMC), and Predictive DTC (P-DTC). …”
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Development of a machine learning-derived dendritic cell signature for prognostic stratification in lung adenocarcinoma by Fang Zhou, Fang Zhou, Meng Wang, Meng Wang, Zheng Wang, Zheng Wang, Wei Li, Wei Li, Xike Lu, Xike Lu

“…A dendritic cell-related signature (DCRS) was constructed using multiple machine learning algorithms (Lasso-Cox, RSF, CoxBoost, Stepwise-Cox), and its prognostic performance was validated in seven external cohorts. …”
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Machine Learning in Maritime Safety for Autonomous Shipping: A Bibliometric Review and Future Trends by Jie Xue, Peijie Yang, Qianbing Li, Yuanming Song, P. H. A. J. M. van Gelder, Eleonora Papadimitriou, Hao Hu

“…Machine learning plays a crucial role in enhancing maritime safety by leveraging its data analysis and predictive capabilities. However, there has been no review grounded in bibliometric analysis in this field. …”
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Dynamic Dwell Time Adjustment in Wire Arc-Directed Energy Deposition: A Thermal Feedback Control Approach by Md Munim Rayhan, Abderrachid Hamrani, Fuad Hasan, Tyler Dolmetsch, Arvind Agarwal, Dwayne McDaniel

“…Future work should focus on integrating multi-axis thermal sensors, extending the framework to multi-material deposition scenarios and implementing machine learning algorithms for predictive thermal modeling.…”
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The role of LAMA5 in breast cancer progression and its potential in immunotherapy by Xiaoli Zhang, Hongfang Yan, Lihan Bie, Zheng Xu, Xiaoyang Yao, Zhilan Li, Chengshan He, Zhouhong Xiang, Xiudi Jiang

“…ROC analysis indicated moderate predictive value for immunotherapy response (AUC = 0.704), and LAMA5 expression was positively associated with sensitivity to chemotherapeutic agents including cisplatin and docetaxel. …”
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A Novel Weighted Fractional GM(1,1) Model and Its Applications by Qin-Qin Shen, Quan Shi, Tian-Pei Tang, Lin-Quan Yao

“…Numerical results show that the new proposed prediction model is very efficient and has both the best fitting accuracy and the best prediction accuracy compared with the GM(1,1) and the FGM(1,1) as well as the NIPGM(1,1) prediction models.…”
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Geographic origin discrimination and quantification of phenolic compounds and moisture in Artemisia argyi folium using NIRS and chemometrics by Lifei Hu, Yifan Wang, Xin Wu, Yuanyuan Shan, Fengxiao Zhu, Fan Zhang, Qiang Yang, Mingxing Liu

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Leveraging Artificial Intelligence and Data Science for Integration of Social Determinants of Health in Emergency Medicine: Scoping Review by Ethan E Abbott, Donald Apakama, Lynne D Richardson, Lili Chan, Girish N Nadkarni

“…NLP models in the reviewed studies displayed significant predictive performance with outcomes, with F1-scores ranging between 0.40 and 0.75 and specificities nearing 95.9%. …”
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Identification of potential pathogenic genes associated with the comorbidity of rheumatoid arthritis and renal fibrosis using bioinformatics and machine learning by Jiao Qiu, Yalin Xu, Luyuan Tong, Xingchun Yang, Xiao Wu

“…A LR model was developed, and its predictive accuracy was verified using the ROC curve derived from an external independent dataset. …”
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Agricultural Machinery Path Tracking with Varying Curvatures Based on an Improved Pure-Pursuit Method by Jiawei Zhou, Junhao Wen, Liwen Yao, Zidong Yang, Lijun Xu, Lijian Yao

“…The current research on path tracking primarily focuses on improving control algorithms, such as adaptive and predictive models, to enhance tracking accuracy and stability. …”
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Spatial-Spectral Linear Extrapolation for Cross-Scene Hyperspectral Image Classification by Lianlei Lin, Hanqing Zhao, Sheng Gao, Junkai Wang, Zongwei Zhang

“…Popular DG strategies constrain the model’s predictive behavior in synthetic space through deep, nonlinear source expansion, and an HSI generation model is usually adopted to enrich the diversity of training samples. …”
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Thyroid nodule classification in ultrasound imaging using deep transfer learning by Yan Xu, Mingmin Xu, Zhe Geng, Jie Liu, Bin Meng

“…In this study, we investigate the predictive efficacy of distinguishing between benign and malignant thyroid nodules by employing traditional machine learning algorithms and a deep transfer learning model, aiming to advance the diagnostic paradigm in this field. …”
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Pediatric sepsis phenotypes for enhanced therapeutics: An application of clustering to electronic health records by Ioannis Koutroulis, Tom Velez, Tony Wang, Seife Yohannes, Jessica E. Galarraga, Joseph A. Morales, Robert J. Freishtat, James M. Chamberlain

“…Additional prospective studies are needed to validate clinical utility of predictive models that target derived pediatric sepsis phenotypes in emergency department settings.…”
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Role of arachidonic acid metabolism in osteosarcoma prognosis by integrating WGCNA and bioinformatics analysis by Yaling Wang, Peichun HSU, Haiyan Hu, Feng Lin, Xiaokang Wei

“…The intersecting genes were identified from weighted gene co-expression network analysis (WGCNA), DEGs (osteosarcoma vs. normal) and DE-AAMRGs (high- vs. low-score). An AA metabolism predictive model of the five AAMRGs were established by Cox regression and the LASSO algorithm. …”
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Gene selection based on adaptive neighborhood-preserving multi-objective particle swarm optimization by Sumet Mehta, Fei Han, Muhammad Sohail, Bhekisipho Twala, Asad Ullah, Fasee Ullah, Arfat Ahmad Khan, Qinghua Ling

“…Traditional optimization algorithms often produce inconsistent and suboptimal results, while failing to preserve local data structures limiting both predictive accuracy and biological interpretability. …”
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Di George syndrome: early diagnosis in pediatric practice by A. A. Pavlikov, I. M. Melnikova, T. I. Pakhomova, N. P. Myakin

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Pharmacological correction of hepatotoxicity induced by anti-tuberculosis drugs by D. S. Sukhanov, E. V. Timofeev, Y. S. Alekseeva, K. A. Nagornova

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Development of Mid-Infrared Spectroscopy (MIR) Diagnostic Model for Udder Health Status of Dairy Cattle by Xiaoli Ren, Chu Chu, Xiangnan Bao, Lei Yan, Xueli Bai, Haibo Lu, Changlei Liu, Zhen Zhang, Shujun Zhang

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Proximal Neural Networks based reconstruction for few-view CT applications by Hoang Trieu Vy Le, Caroline Bossuyt, Julie Escoda, Marius Costin, Jan De Beenhouwer, Jan Sijbers

“…Recent advancements in Plug-and-Play (PnP) algorithms have shown promise for solving imaging inverse problems by utilizing the capabilities of Gaussian denoising algorithms to handle complex optimization tasks. …”
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