Machine learning-based forecasting of ground surface settlement induced by metro shield tunneling construction by Qiankun Wang, Chuxiong Shen, Chao Tang, Zeng Guo, Fangqi Wu, Wenyi Yang

“…The maximum relative error of the prediction based on the data preprocessing method and PSO-BP algorithm is 0.46%, demonstrating a good fitting effect. …”
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Impact of ITH on PRAD patients and feasibility analysis of the positive correlation gene MYLK2 applied to PRAD treatment by Chuanyu Ma, Chuanyu Ma, Guandu Li, Xiaohan Song, Xiaochen Qi, Tao Jiang

“…GO and KEGG pathway enrichment analyses were performed on these 103 positively correlated differentially expressed genes, and the proportion and type of tumour-infiltrating immune cells were assessed by TIMER, CIBERSORT, CIBERSORT-ABS, QUANTISEQ, MCPCOUNTER, XCELL and EPIC algorithms in patients. In addition, we calculated the relevance of immunotherapy and predicted various drugs that might be used for treatment and evaluated the predictive power of survival models under multiple machine learning algorithms through the training set TCGA-PRAD versus the validation set PRAD-FR cohort. …”
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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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The application of compressed sensing on tumor mutation burden calculation from overlapped pooling sequencing data by Yue Cui, Yi Qiao, Rongming An, Xuan Pan, Jing Tu

“…Based on this, the orthogonal matching pursuit (OMP) algorithm and the basic pursuit (BP) algorithm were used to reconstruct TMB from pooling sequencing data. …”
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Characterizing and mapping the spatial variability of HIV risk among adolescent girls and young women: A cross-county analysis of population-based surveys in Eswatini, Haiti, and M... by Kristen N Brugh, Quinn Lewis, Cameron Haddad, Jon Kumaresan, Timothy Essam, Michelle S Li

“…Using geolocated survey data at enumeration clusters and high-resolution satellite imagery, we applied algorithms to predict the number and proportion of at-risk AGYW at hyperlocal levels.…”
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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

“…Results The neural network model outperformed traditional interpolation techniques, achieving a 47% reduction in Root Mean Square Error (RMSE), and a 0.56 increase in R2 compared to the best-performing IDW variant (RS-IDW). …”
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Machine-Learning-Driven Approaches for Assessment, Delegation, and Optimization of Multi-Floor Building by Abtin Baghdadi, Harald Kloft

“…The significance of this research lies in its ability to automate and accelerate complex structural analysis using Adaptive Neuro-Fuzzy Inference Systems (ANFISs), achieving an average error of less than 2% in multi-variable prediction scenarios. The results were compared against reference calculations and ETABS simulations to validate its effectiveness, demonstrating deviations of less than 3%. …”
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Impurity rates detection for pepper harvesting based on YOLOv8n-Seg-ASB and random forest by Lijian Lu, Jin Lei, Chenming Cheng, Shiguo Wang, Chengfu Wang, Xinyan Qin

“…Finally, a random forest (RF) model is constructed to predict impurity rates by incorporating features such as mask pixel area, fitting length, fitting width and mask perimeter. …”
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Machine learning for epithelial ovarian cancer platinum resistance recurrence identification using routine clinical data by Li-Rong Yang, Mei Yang, Liu-Lin Chen, Yong-Lin Shen, Yuan He, Zong-Ting Meng, Wan-Qi Wang, Feng Li, Zhi-Jin Liu, Lin-Hui Li, Yu-Feng Wang, Xin-Lei Luo

“…Following this screening process, five machine learning algorithms were employed to develop predictive models based on the selected variables. …”
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Industrial multi-machine data aggregation, AI-ready data preparation, and machine learning for virtual metrology in semiconductor wafer and slider production by Feiyang Ou, Julius Suherman, Chao Zhang, Henrik Wang, Sthitie Bom, James F. Davis, Panagiotis D. Christofides

“…Smart Manufacturing (SM), which is short for “Smart (Predictive, Preventive, Proactive) zero incident, zero emissions Manufacturing,” describes manufacturing’s digital transformation in which factories, supply chains and ecosystems are integrated, interoperable, and interconnected. …”
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Spectroscopic photoacoustic denoising framework using hybrid analytical and data-free learning method by Fangzhou Lin, Shang Gao, Yichuan Tang, Xihan Ma, Ryo Murakami, Ziming Zhang, John D. Obayemi, Winston O. Soboyejo, Haichong K. Zhang

“…Advanced methods, including learning-based approaches and analytical algorithms, have demonstrated promise but often require extensive training data and parameter tuning. …”
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Application of inertial navigation high precision positioning system based on SVM optimization by Ruiqun Han

“…In addition, support vector machines were used to optimize pedestrian trajectory prediction algorithms, and a pedestrian motion state recognition algorithm was designed based on this. …”
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Neural Network-Based Imitation Learning for Approximating Stochastic Battery Management Systems by Andrea Pozzi, Alessandro Incremona, Daniele Toti

“…Specifically, the proposed method leverages the Dataset Aggregation algorithm to overcome the issue of distributional shift, a common limitation in imitation learning frameworks. …”
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The role of neurovisualization in monitoring stroke risk among athletes: a review by Bauyrzhan Omarov, Akbayan Aliyeva

“…Results: the main results indicated that imaging biomarkers such as microbleeds, perfusion deficits, and white matter disruptions could be effectively detected and interpreted using artificial intelligence models. wearable data integrated with neuroimaging further enhanced the precision of predictive assessments. Discussion: the findings were consistent with previous studies that supported the use of multimodal imaging and computational tools in stroke risk evaluation. however, data heterogeneity and algorithmic transparency were identified as persistent challenges across the reviewed literature. …”
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Feature selection‐based android malware adversarial sample generation and detection method by Xiangjun Li, Ke Kong, Su Xu, Pengtao Qin, Daojing He

“…Prediction results obtained by the two classification algorithms are integrated based on certain rules. …”
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CFD-Guided Design of Non-Uniform Flow Channels in PEMFCs for Waste Heat Utilization in District Heating Networks by Dai Cui, Dong Liu, Peng Yu, Jiayi Li, Zhi Zhou, Meishan Zhang, Qun Chen, Fang Yuan

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A Field-Programmable Gate Array-Based Adaptive Sleep Posture Analysis Accelerator for Real-Time Monitoring by Mangali Sravanthi, Sravan Kumar Gunturi, Mangali Chinna Chinnaiah, Siew-Kei Lam, G. Divya Vani, Mudasar Basha, Narambhatla Janardhan, Dodde Hari Krishna, Sanjay Dubey

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Lightweight defocus deblurring network for curved-tunnel line scanning using wide-angle lenses by Shaojie Qin, Taiyue Qi, Xiaodong Huang, Xiao Liang

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Application of the Integral Energy Criterion and Neural Network Model for Helicopter Turboshaft Engines’ Vibration Characteristics Analysis by Serhii Vladov, Maryna Bulakh, Denys Baranovskyi, Eduard Kisiliuk, Victoria Vysotska, Maksym Romanov, Jan Czyżewski

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Deterministic cascade evolution in coal and gas outbursts: From early acoustic signatures to system-wide failure by Yang Lei, Zhijie Wen, Liang Wang, Ting Ren, Yujun Zuo

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