GNSS-RTK-Based Navigation with Real-Time Obstacle Avoidance for Low-Speed Micro Electric Vehicles by Nuksit Noomwongs, Kanin Kiataramgul, Sunhapos Chantranuwathana, Gridsada Phanomchoeng

“…The system employs a scored predicted trajectory algorithm that simultaneously optimizes path-following accuracy and obstacle evasion. …”
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A prognostic glycolysis-related gene signature in osteosarcoma: implications for metabolic programming, immune microenvironment, and drug response by Naiqiang Zhu, Jingyi Hou, Yu Zhang, Ning Yang, KaiKai Ding, Chengbing Chang, Yanqi Liu, Haipeng Gu, Bin Chen, Xu Wei, Liguo Zhu

“…The prognostic efficacy of this risk signature was assessed via Kaplan–Meier curve analysis and Cox regression, evaluating its independence as a prognostic indicator. Additionally, the predictive potential of the risk model for drug response was evaluated using the “OncoPredict” package. …”
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Genome-wide profiling of circulating microRNAs in adolescent idiopathic scoliosis and their relation to spinal deformity severity, and disease pathophysiology by Nasrin Khatami, Iurie Caraus, Mahamuda Rahaman, Evguenia Nepotchatykh, Mohamed Elbakry, Wesam Elremaly, Anita Franco, Marie Beauséjour, Anne-Marie Laberge, Stefan Parent, Hubert Labelle, Carl-Éric Aubin, Jean Lachaine, Alain Moreau

“…After optimization and the application of Random Forest Models a panel of six miRNAs (miR-1-3p, miR-19a-3p, miR-19b-3p, miR-133b, miR-143-3p, and miR-148b-3p) out of 15 led us to develop an algorithm predicting the risk of developing a severe scoliosis with great accuracy (100%), sensitivity (100%) and specificity (100%). …”
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LcProt: Proteomics‐based identification of plasma biomarkers for lung cancer multievent, a multicentre study by Hengrui Liang, Runchen Wang, Ran Cheng, Zhiming Ye, Na Zhao, Xiaohong Zhao, Ying Huang, Zhanpeng Jiang, Wangzhong Li, Jianqi Zheng, Hongsheng Deng, Yu Jiang, Yuechun Lin, Yun Yan, Lei Song, Jie Li, Xin Xu, Wenhua Liang, Jun Liu, Jianxing He

“…ABSTRACT Background Plasma protein has gained prominence in the non‐invasive predicting of lung cancer. We utilised Zeolite Zotero NaY‐based plasma proteomics to investigate its potential for multiple event predicting, including lung cancer diagnosis (task #1), lymph node metastasis detection (task #2) and tumour‒node‒metastasis (TNM) staging (task #3). …”
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The relationship between the expression of serum asprosin and miR-21 in patients with osteoporosis and delayed healing after OVCF surgery by Gaoming Song, Silong Lin, Xianqi Zhang, Hong Pan

“…A nomogram model was constructed to predict delayed healing, and its predictive value was evaluated using the receiver operating curve (ROC) analysis. …”
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Machine learning model for differentiating malignant from benign thyroid nodules based on the thyroid function data by Quan Zhou, Lihua Zhang, Nan Xiang, Lele Zhang, Fuqiang Ma, Fengchang Yu, Shenhui Lv, Zhilin Lu, He-Rong Mao

“…FT4, TPOAB and FT3 were validated as the top three features in the Gradient Boosting model.Conclusions This study innovatively developed a predictive model for benign and malignant TNs based on the Gradient Boosting Decision Tree algorithm. …”
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LYN and CYBB are pivotal immune and inflammatory genes as diagnostic biomarkers in recurrent spontaneous abortion by Zhuna Wu, Qiuya Lin, Zhimei Zhou, Yajing Xie, Li Huang, Liying Sheng, Qirong Shi, Yumin Ke

“…The performance of the predictive model was evaluated using a Nomo plot. We further confirmed the expression levels and diagnostic value of key genes by performing immunohistochemistry (IHC) in clinical tissue samples. …”
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Advancing a machine learning-based decision support tool for pre-hospital assessment of dyspnoea by emergency medical service clinicians: a retrospective observational study by Wivica Kauppi, Henrik Imberg, Johan Herlitz, Oskar Molin, Christer Axelsson, Carl Magnusson

“…The gradient boosting algorithm had the overall best performance, with excellent calibration of the predictions, and consistently showed higher sensitivity to detect SAE than the other methods. …”
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An English Diagnostic Intelligence Evaluation Model Based on Organizational Evolutionary Information Entropy by Haiying Sang

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Symbolic Computation and the Extended Hyperbolic Function Method for Constructing Exact Traveling Solutions of Nonlinear PDEs by Huang Yong, Shang Yadong, Yuan Wenjun

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A Path-Driven Fluid Routing and Scheduling Method for Continuous-Flow Microfluidic Biochips with Delay Time Optimization by Zhisheng Chen, Bowen Liu, Hongjin Su, Zhen Chen, Genggeng Liu, Xing Huang

“…For routing, we develop a hybrid particle swarm optimization algorithm that incorporates conflict awareness and channel utilization strategies. …”
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Design and Multi-Objective Optimization of Auxetic Sandwich Panels for Blastworthy Structures Using Machine Learning Method by Andika, Sigit Puji Santosa, Djarot Widagdo, Arief Nur Pratomo

“…Optimization is carried out using the nondominated sorting genetic algorithm II (NSGA-II) method. The optimization results show significant improvements in blastworthiness performance, with notable reductions in permanent displacement and enhancements in specific energy absorption (SEA). …”
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Potato late blight leaf detection in complex environments by Jingtao Li, Jiawei Wu, Rui Liu, Guofeng Shu, Xia Liu, Kun Zhu, Changyi Wang, Tong Zhu

“…To help detect this disease in complex environments, an improved YOLOv5 algorithm is proposed. First, ShuffleNetV2 is used as the backbone network to reduce the number of parameters and computational load, making the model more lightweight. …”
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Core-periphery structure for district metered area partitioning in urban water distribution systems by Rair Solis Jacome, Thomaz Anchieta, Bruno M. Brentan, Manuel Herrera, Xitlali Delgado Galvan, Jose Antonio Arciniega Nevarez, Jesus Mora Rodriguez

“…When applied to the Modena WDN in Italy, this approach demonstrates improved pressure stability and significant cost reductions compared to traditional methods. Overall, the findings highlight the practical benefits of the core-periphery-based DMA design, offering a scalable and data-driven solution for urban water distribution systems.…”
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Assessing glacier thickness changes with multi-temporal UAV-derived DEMs: The evolution of Forni Glacier over the period 2014–2022 by Valeria Belloni, Davide Fugazza, Kevin Hanson, Marco Scaioni, Martina Di Rita

“…The comparison of co-registered DEM highlighted glacier thickness losses at the terminus reaching 50 m, with side areas showing smaller reductions of around 25 m between 2014 and 2022.…”
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Cooperative control method for multi-agent ground fracturing truck group based on offline reinforcement learning by RuYi Wang, HuiShen Jiao, YingCheng Tian, Yi Zhao, SiQi Wang, Ke Zhang, Bo Huang, QinRui Sun, DanDan Zhu

“…The core of this method is an improved algorithm based on the TD3, which is enhanced by the incorporation of the CQL algorithm to improve the stability of the collaborative control strategy. …”
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Improved analysis with spectral-domain optical coherence tomography angiography for evaluating vascular damage in exfoliation syndrome by Rongpei Zhang, Bingying Lin, Hairui Zhang, Yuncheng Ma, Na Xu, Ling Jin, Zhenyu Wang, Lei Tian, Munire Mohetaer, Aizezi Wumaier, Rongxin Chen, Danping Huang

“…The areas under the receiver operating characteristic curve for the SVC FAZ area and OS VD in predicting XFS were both >0.67. Conclusions: The pixel-level FAZ algorithm and VD map derived from OCTA can reflect microvascular damage in XFS. …”
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Clinical significance of a machine learning model based on short-term changes in NT-proBNP after TAVR by Yu Mao, Mengen Zhai, Ping Jin, Gejun Zhang, Haibo Zhang, Lai Wei, Xiaoke Shang, Jian Liu, Yingqiang Guo, Xiangbin Pan, Yang Liu, Jian Yang

“…The 4-year primary end-point rates in the four groups were 13.1 %, 18.0 %, 26.9 %, and 33.3 % (log-rank, p < 0.001). A model for predicting the incidence of the primary end point was based on the random forest algorithm. …”
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Hygienic substantiation of calculating models for prognosis of toxicity of different classes insecticides (second part) by O.P. Vavrinevych, B.I. Shpak, A.M. Antonenko, S.T. Omelchuk, T.I. Zinchenko

“…The purpose of the research is the scientific substantiation and statistical analysis of the calculation models for predicting the toxicity of insecticides of different classes. …”
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Machine learning-based detoxification enzymes-related genes prognosis model in breast cancer: immune landscape and clinical significance by Jingdi Zhang, Wendi Zhan, Haihong Hu, Hongxia Zhu, Bo Hao, Siyu Wang, Zhuo Li, Zhiming Zhang, Taolan Zhang

“…Lasso cox regression analysis and univariate and multivariate Cox analysis were used to process the data, and machine learning algorithm was used to construct breast cancer prognosis model. …”
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