The underlying molecular mechanisms and biomarkers of Hip fracture combined with deep vein thrombosis based on self sequencing bioinformatics analysis by Guanghua Shi, Xiaocui Shi, Meng Zhang, Rui Cheng, Mengqing Hu, Yu Zhao, Shimei Li, Xiuxiu Li, Haiyun Ma, Pengcui Li

“…Feature genes were further refined by intersecting results from three machine learning algorithms and constructing an artificial neural network (ANN). …”
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Single cell transcriptomic analysis reveals tumor immune infiltration by macrophage cells gene signature in lung adenocarcinoma by Xiaotong Guo, Youjun Deng, Wenjun Jiang, Heng Li, Yisheng Luo, Huachuan Zhang, Hao Wu

“…High TGS tumors exhibited enrichment in TGF-β signaling and hypoxia pathways, suggesting their potential utility in predicting prognosis and immune responses in patients with LUAD. …”
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Research Status and Development Trends of Deep Reinforcement Learning in the Intelligent Transformation of Agricultural Machinery by Jiamuyang Zhao, Shuxiang Fan, Baohua Zhang, Aichen Wang, Liyuan Zhang, Qingzhen Zhu

“…From the perspective of algorithm–hardware synergy, the article provides an in-depth analysis of DRL’s specific applications in agricultural ground platform navigation, path planning for intelligent agricultural end-effectors, and autonomous operations of low-altitude unmanned aerial vehicles. …”
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Identifying mating events of group-housed broiler breeders via bio-inspired deep learning models by Venkat U.C. Bodempudi, Guoming Li, J. Hunter Mason, Jeanna L. Wilson, Tianming Liu, Khaled M. Rasheed

“…The DLM framework included a bird detection model, data filtering algorithms based on mating duration, and logic frameworks for mating identification based on bird count changes. …”
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Aneuploidy screening in women of advanced age in the public healthcare setting of a low- to middle- income country – an observational cohort study by L Geerts, N Du Toit, M Schoeman

“…In the SA public sector, DS screening and confirmatory genetic testing are fully state subsidised for women of advanced maternal age (AMA) but, owing to the low positive predictive value of AMA-based screening, ultrasound-based screening is also offered. …”
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A capable numerical scheme for solving nonlinear Volterra delay integral equations of the third kind by Rohollah Ghaedi Ghalini, Esmail Hesameddini, Hojatollah Laeli Dastjerdi

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Machine learning identification of a novel vasculogenic mimicry-related signature and FOXM1’s role in promoting vasculogenic mimicry in clear cell renal cell carcinoma by Chao Xu, Sujing Zhang, Jingwei Lv, Yilong Cao, Yao Chen, Hao Sun, Shengtao Dai, Bowei Zhang, Meng Zhu, Yuepeng Liu, Junfei Gu

“…The predictive value of VRG_score for ccRCC prognosis and treatment response was assessed. …”
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Deep Learning Based Large‐Area Contact Sensing for Safe Human–Robot Interaction Using Conformal Kirigami Structure‐Enabled Robotic E‐Skin by Rui Jiao, Zhengjun Wang, Ruoqin Wang, Qian Xu, Jiacheng Jiang, Boyang Zhang, Simin Yang, Yang Li, Yik Kin Cheung, Fan Shi, Hongyu Yu

“…Additionally, a convolutional neural network‐based deep learning algorithm is implemented to decode the features of guided wave signals and predict the contact location and energy intensity on the robot surface. …”
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The Forecasting Yield of Highland Barley and Wheat by Combining a Crop Model with Different Weather Fusion Methods in the Study of the Northeastern Tibetan Plateau by Peng Li, Liang He, Xuetong Wang, Mengfan Zhao, Fan Li, Ning Jin, Ning Yao, Chao Chen, Qi Tian, Bin Chen, Gang Zhao, Qiang Yu

“…For HB, sequential selection and an improved KNN algorithm were optimal, while for wheat, sequential selection performed best. …”
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Identifying key drivers of heatwaves: A novel spatio-temporal framework for extreme event detection by J. Pérez-Aracil, C. Peláez-Rodríguez, Ronan McAdam, Antonello Squintu, Cosmin M. Marina, Eugenio Lorente-Ramos, Niklas Luther, Verónica Torralba, Enrico Scoccimarro, Leone Cavicchia, Matteo Giuliani, Eduardo Zorita, Felicitas Hansen, David Barriopedro, Ricardo García-Herrera, Pedro A. Gutiérrez, Jürg Luterbacher, Elena Xoplaki, Andrea Castelletti, S. Salcedo-Sanz

“…A novel framework named Spatio-Temporal Cluster-Optimized Feature Selection (STCO-FS) is proposed to identify key immediate (short-term) HW drivers by combining clustering algorithms with an ensemble evolutionary algorithm. …”
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Race course characteristics are the most important predictors in 48 h ultramarathon running by Beat Knechtle, David Valero, Elias Villiger, Katja Weiss, Pantelis T. Nikolaidis, Lorin Braschler, Rodrigo Luiz Vancini, Marilia Santos Andrade, Ivan Cuk, Thomas Rosemann, Mabliny Thuany

“…A machine learning (ML) model based on the XG Boost algorithm was built to predict running speed from the athlete´s age, gender, country of origin, where the race occurs and race course characteristic such as elevation (flat or hilly) and surface (asphalt, cement, granite, grass, gravel, sand, track, or trail). …”
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Multi-scenario analysis of green water resource efficiency under carbon emission constraints in the Chengdu-Chongqing urban agglomeration, China: A system dynamics approach by Keyao Yu, Zhigang Li

“…Five scenarios are then set up: baseline development, economic priority, green innovation, water-saving and emission reduction, and comprehensive development. These scenarios are used to simulate and predict different development paths and evaluate the impact of various key indicators on GWRE. …”
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Stacking data analysis method for Langmuir multi-probe payload by Jin Wang, Jin Wang, Duan Zhang, Qinghe Zhang, Qinghe Zhang, Xinyao Xie, Fangye Zou, Qingfu Du, Qingfu Du, V. Manu, Yanjv Sun

“…This study uses a stacking algorithm to process m-NLP data and incorporates the International Reference Ionosphere (IRI) model to correct the predicted electron density (Ne) values. …”
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Use of artificial intelligence to support prehospital traumatic injury care: A scoping review by Jake Toy, Jonathan Warren, Kelsey Wilhelm, Brant Putnam, Denise Whitfield, Marianne Gausche‐Hill, Nichole Bosson, Ross Donaldson, Shira Schlesinger, Tabitha Cheng, Craig Goolsby

“…The most common study objectives were to predict the need for critical care and life‐saving interventions (29%), assist in triage (22%), and predict survival (20%). …”
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Leveraging Machine Learning and Remote Sensing for Water Quality Analysis in Lake Ranco, Southern Chile by Lien Rodríguez-López, Lisandra Bravo Alvarez, Iongel Duran-Llacer, David E. Ruíz-Guirola, Samuel Montejo-Sánchez, Rebeca Martínez-Retureta, Ernesto López-Morales, Luc Bourrel, Frédéric Frappart, Roberto Urrutia

“…This study examines the dynamics of limnological parameters of a South American lake located in southern Chile with the objective of predicting chlorophyll-a levels, which are a key indicator of algal biomass and water quality, by integrating combined remote sensing and machine learning techniques. …”
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Analysis of the molecular nature associated with microsatellite status in colon cancer identifies clinical implications for immunotherapy by Wei Wu, Qihan Fu, Lulu Liu, Yi Zheng, Hangyu Zhang, Peng Zhao, Weijia Fang, Xuanwen Bao, Shaobing Cheng, Xiaomeng Dai, Xudong Zhu, Zhou Tong, Fanglong Liu

“…A more homogeneous highly expressed pattern of PD1 was observed in CD8+ T cells from MSI colon cancer; however, a small subgroup of CD8+ T cells with high expression of checkpoint molecules was identified in MSS patients. A random forest algorithm predicted important mutations that were associated with MSI status in the TCGA colon cancer cohort, and our in-house cohort validated higher frequencies of BRAF, ARID1A, RNF43, and KM2B mutations in MSI colon cancer. …”
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Intrusion Detection System Based on Decision Tree and Clustered Continuous Inputs by Adel Issa

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The repertory grids method in the investigation of cognitive differentiation in the sphereof communication by T. G. Siroshtanenko

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Comprehensive Transcriptome Sequencing and Analysis of <i>Euspira gilva</i>: Insights into Aquaculture and Conservation by Zhixing Su, Jiayuan Xu, Xiaokang Lv, Xuefeng Song, Yanming Sui, Benjian Wang, Xiaoshan Wang, Bianbian Zhang, Baojun Tang, Liguo Yang

“…A total of 7929 simple sequence repeat (SSR) loci were identified, with single nucleotide repeats predominating at 85.0%. Predictive analysis of coding DNA sequences (CDS) resulted in 1340 BLAST comparisons, while ESTScan predicted 840. …”
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Quantifying Uncertainties in Solar Wind Forecasting due to Incomplete Solar Magnetic Field Information by Stephan G. Heinemann, Jens Pomoell, Ronald M. Caplan, Mathew J. Owens, Shaela Jones, Lisa Upton, Bibhuti Kumar Jha, Charles N. Arge

“…Solar wind forecasting plays a crucial role in space weather prediction, yet significant uncertainties persist duet to incomplete magnetic field observations of the Sun. …”
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