Machine learning technique-based four-autoantibody test for early detection of esophageal squamous cell carcinoma: a multicenter, retrospective study with a nested case–control stu... by Yi-Wei Xu, Yu-Hui Peng, Can-Tong Liu, Hao Chen, Ling-Yu Chu, Hai-Lu Chen, Zhi-Yong Wu, Wen-Qiang Wei, Li-Yan Xu, Fang-Cai Wu, En-Min Li

“…Then, we validated the ability of plsRglm model in predicting preclinical ESCC by a nested case–control study (24 preclinical ESCCs and 112 matched controls) within a population-based prospective cohort study. …”
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COMMUNICATIVE TOOLS FOR COUNTERING MISINFORMATION by Vladyslav Voichuk

“…At the same time, digital technologies such as data analysis algorithms or artificial intelligence offer new opportunities to combat fakes. …”
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Efficient Resources Provisioning Based on Load Forecasting in Cloud by Rongdong Hu, Jingfei Jiang, Guangming Liu, Lixin Wang

“…It integrates an improved support vector regression algorithm and Kalman smoother. Public trace data taken from multitypes of resources were used to verify its prediction accuracy, stability, and adaptability, comparing with AR, BPNN, and standard SVR. …”
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MAD-RAPPEL: Mobility Aware Data Replacement And Prefetching Policy Enrooted LBS by Ajay K. Gupta, Udai Shanker

“…The cache replacement and invalidation module uses the next location prediction algorithm by the application of the mobility Markov model on mobile user’s trajectories. …”
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Radar Working State Recognition Based on Improved HPSO-BP by Huiqin Li, Yanling Li, Xuemei Wang, Zhe Xu, Xinli Yin

“…First, the model improves the HPSO algorithm through the nonlinear decreasing inertia weight by adding the deceleration factor and asynchronous learning factor. …”
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Metabolic network segmentation: A probabilistic graphical modeling approach to identify the sites and sequential order of metabolic regulation from non-targeted metabolomics data. by Andreas Kuehne, Urs Mayr, Daniel C Sévin, Manfred Claassen, Nicola Zamboni

“…We present the metabolic network segmentation (MNS) algorithm, a probabilistic graphical modeling approach that enables genome-scale, automated prediction of regulated metabolic reactions from differential or serial metabolomics data. …”
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Deep Reinforcement Learning Method for Wireless Video Transmission Based on Large Deviations by Yongxiao Xie, Shian Song

“…To further optimize resources in wireless energy transmission and tackle the challenge of balancing exploration and exploitation in the DRL algorithm, this paper develops an adaptive DRL algorithm that extends classical DRL frameworks by integrating dropout techniques during both the training and prediction processes. …”
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Glucagon-like peptide-1 receptor agonist use prior to spinal surgery results in reduced postoperative length of stay: A propensity-score matched analysis by Samuel N. Goldman, BS, Kyle Mani, BE, Thomas Scharfenberger, BS, Emily Kleinbart, BA, Aaron T. Hui, BS, Rafael De la Garza Ramos, MD, Mitchell S. Fourman, MD, MPhil, Ananth S. Eleswarapu, MD

“…GLP-1 RA use was associated with a significant reduction in median postoperative LOS (3 days vs. 4 days; p = 0.036), particularly among patients undergoing lumbar fusion. …”
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Associations of choroid plexus volume with white matter hyperintensity volume and susceptibility and plasma amyloid markers in cerebral small vessel disease by Pengcheng Liang, Meng Li, Yiwen Chen, Zhenyu Cheng, Na Wang, Yuanyuan Wang, Nan Zhang, Yena Che, Jing Li, Changhu Liang, Lingfei Guo

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A Universal Tire Detection Method Based on Improved YOLOv8 by Chi Guo, Mingxia Chen, Junjie Wu, Haipeng Hu, Luobing Huang, Junjie Li

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Modeling, Validation and Analysis of the Performance of Direct Air-Cooling Condensers for Mountainous Terrain by Xubo Lu, Hongyi Chen, Jingyao Wang, Huimin Wei, Xiaoze Du

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Research on the Method of Coke Optical Tissue Segmentation Based on Adaptive Clustering by Huaiguang Liu, Liheng Zhang, Shiyang Zhou, Li Fang

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Methods to Quantitatively Evaluate the Effect of Shale Gas Fracturing Stimulation Based on Least Squares by DENG Cai, SUN Kexin, WEN Huan, HU Chaolang

“…Advanced optimization algorithms were employed to efficiently address both the fitting and calculation tasks. …”
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POSSIBILITIES OF CARIES PROGNOSIS IN CHILDREN OF SCHOOL-AGE ACCORDING TO DATA GAINED FROM THEM AND THEIR PARENTS QUESTIONNAIRE by L.F. Kaskova, T.B. Mandziuk, L.P. Ulasevych, L.D. Korovina, M.A. Sadovski

“…Therefore, the purpose of our study was to identify the possibility of predicting caries in preschool children according to questionnaires of surveyed children and their parents. …”
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Optimization of Adversarial Reprogramming for Transfer Learning on Closed Box Models by Alexander Bott, Moritz Siems, Alexander Puchta, Jurgen Fleischer

“…In this work, we optimise a transfer learning approach for predicting the Remaining Useful Life (RUL) of ball bearings, particularly in scenarios with limited data availability. …”
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Physics-Informed Neural Network for Load Margin Assessment of Power Systems with Optimal Phasor Measurement Unit Placement by Murilo Eduardo Casteroba Bento

“…The results achieved demonstrate the benefits of inserting physical knowledge in the PINN training and the optimal selection of PMUs at system buses for load margin prediction.…”
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Chaotic Behaviors and Coexisting Attractors in a New Nonlinear Dissipative Parametric Chemical Oscillator by Y. J. F. Kpomahou, A. Adomou, J. A. Adéchinan, A. E. Yamadjako, I. V. Madogni

“…The performed numerical simulations confirm the obtained analytical predictions. Second, the prediction of coexisting attractors is investigated by solving numerically the new nonlinear parametric ordinary differential equation via the fourth-order Runge–Kutta algorithm. …”
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Informing antimicrobial stewardship with explainable AI. by Massimo Cavallaro, Ed Moran, Benjamin Collyer, Noel D McCarthy, Christopher Green, Matt J Keeling

“…An appropriately trained gradient boosted decision tree algorithm, supplemented by a Shapley explanation model, predicts the likely antimicrobial drug resistance, with the odds of resistance informed by characteristics of the patient, admission data, and historical drug treatments and culture test results. …”
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FAULT DIAGNOSIS NEW METHOD OF ROLLING BEARING BASED ON ADAPTIVE REDUNDANT LIFTING SCHEME PACKET by XIAO ShunGen, SONG MengMeng, LAI LianFeng

“…Aiming at feature identification of weak signal for rolling bearing fault,an adaptive redundant lifting scheme packet（ ARLSP） diagnostic method of undecimated operation was proposed to solve the faults distortion that caused by traditional wavelet packet or lifting wavelet transform using sample operation.ARLSP was based on the principle of lifting scheme.Initial undecimated prediction and update operator were calculated by Lagrange interpolating subdivision,and then constructed an ARLSP decomposition and reconstruction algorithm.Simulation signals were tried out by denoising and anti frequency aliasing,results show that ARLSP method was superior to the traditional wavelet packet in denoising capabilities,and there are no frequency aliasing.Moreover,taking an experiment on an asynchronous motor,the vibration signals of the rolling bearings 6205 under conditions of no fault,the inner ring fault,outer ring fault and rolling fault were measured.ARLSP method has been successfully used to extract characteristic frequency and frequency multiplication for various faults,and has got a higher diagnostic accuracy than traditional wavelet packet.…”
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Deepfake Dilemmas: Imagine Tomorrow’s Surveillance Society through Three Scenarios by Fatma Doğan Akkaya

“…Moving beyond technical considerations, the research employs social prediction methods to explore three potential future scenarios involving deepfake avatars: seamless integration that facilitates self-expression but complicates digital identity control; pervasive algorithmic surveillance that exacerbates social control and privacy issues; and the concept of ghost avatars, that is, digital representations that function as commodities or tools of resistance. …”
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